38 results back to index
Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth by Stuart Ritchie
Albert Einstein, anesthesia awareness, Bayesian statistics, Carmen Reinhart, Cass Sunstein, citation needed, Climatic Research Unit, cognitive dissonance, complexity theory, coronavirus, correlation does not imply causation, COVID-19, Covid-19, crowdsourcing, deindustrialization, Donald Trump, double helix, en.wikipedia.org, epigenetics, Estimating the Reproducibility of Psychological Science, Growth in a Time of Debt, Kenneth Rogoff, l'esprit de l'escalier, meta analysis, meta-analysis, microbiome, Milgram experiment, mouse model, New Journalism, p-value, phenotype, placebo effect, profit motive, publication bias, publish or perish, race to the bottom, randomized controlled trial, recommendation engine, rent-seeking, replication crisis, Richard Thaler, risk tolerance, Ronald Reagan, Scientific racism, selection bias, Silicon Valley, Silicon Valley startup, Stanford prison experiment, statistical model, stem cell, Steven Pinker, Thomas Bayes, twin studies, University of East Anglia
If the medical literature gives doctors an inflated view of how much benefit a drug provides (as indeed appears to have been the case for antidepressants, which do seem to work, but not with as strong an effect as initially believed), their clinical reasoning will be knocked off track.32 If you hadn’t heard of publication bias before now, it would be perfectly understandable: it is one of science’s more embarrassing secrets. But a 2014 survey of reviews in top medical journals found that 31 per cent of meta-analyses didn’t even check for it. (Once it was properly checked for, 19 per cent of those meta-analyses indicated that publication bias was indeed present.)33 A later review of cancer-research reviews was even worse: 72 per cent didn’t include publication bias checks.34 It’s often hard to know exactly what to do when you find hints of publication bias in your meta-analytic dataset – should you revise the estimate of the average effect downwards? If so, by how much?35 – but it’s doubtful that the proper answer is to ignore the issue entirely.
Akira Onishi & Toshi A. Furukawa, ‘Publication Bias Is Underreported in Systematic Reviews Published in High-Impact-Factor Journals: Metaepidemiologic Study’, Journal of Clinical Epidemiology 67, no. 12 (Dec. 2014): pp. 1320–26, https://doi.org/10.1016/j.jclinepi.2014.07.002 34. D. Herrmann et al., ‘Statistical Controversies in Clinical Research: Publication Bias Evaluations Are Not Routinely Conducted in Clinical Oncology Systematic Reviews’, Annals of Oncology 28, no. 5 (May 2017): pp. 931–37; https://doi.org/10.1093/annonc/mdw691 35. There’s a whole set of techniques to adjust the effect size in your meta-analysis when you discover that there’s publication bias. Since these are guesswork (about how much you should reduce the effect size) stacked on guesswork (about how much publication bias there is), I always feel a bit nervous about using them.
35 – but it’s doubtful that the proper answer is to ignore the issue entirely. The trouble with the archaeological approach to publication bias is that it relies on conjecture to fill in the gaps in the funnel plot – those places where we would expect the small studies with small effects to appear. Funnel plots can have weird shapes for reasons other than publication bias, especially if there are a lot of differences between the assorted studies that go into the meta-analysis.36 There are many cases where publication bias is more subtle, and thus harder to discern, than in those described above. Are there better ways to check for this kind of bias? One alternative approach would be to take a set of studies you know for sure were completed, with a range of results from strongly positive to null, then check how many of each type made it through to get published.
Bad Pharma: How Medicine Is Broken, and How We Can Fix It by Ben Goldacre
data acquisition, framing effect, if you build it, they will come, illegal immigration, income per capita, meta analysis, meta-analysis, placebo effect, publication bias, randomized controlled trial, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), Simon Singh, WikiLeaks
Health Technol Assess. 2010 Feb;14(8):iii, ix–xi, 1–193. 23 Dickersin K. How important is publication bias? A synthesis of available data. Aids Educ Prev 1997;9(1 SA):15–21. 24 Ioannidis J. Effect of the statistical significance of results on the time to completion and publication of randomized efficacy trials. JAMA 1998;279:281–6. 25 Bardy AH. Bias in reporting clinical trials. Brit J Clin Pharmaco 1998;46:147–50. 26 Dwan K, Altman DG, Arnaiz JA, Bloom J, Chan AW, Cronin E, et al. Systematic review of the empirical evidence of study publication bias and outcome reporting bias. PLoS ONE 2008;3(8):e3081. 27 Decullier E, Lhéritier V, Chapuis F. Fate of biomedical research protocols and publication bias in France: retrospective cohort study. BMJ 2005;331:19. Decullier E, Chapuis F. Impact of funding on biomedical research: a retrospective cohort study.
Systematically taking all the evidence that we have so far, what do we see overall? It’s not ideal to lump every study of this type together in one giant spreadsheet, to produce a summary figure on publication bias, because they are all very different, in different fields, with different methods. This is a concern in many meta-analyses (though it shouldn’t be overstated: if there are lots of trials comparing one treatment against placebo, say, and they’re all using the same outcome measurement, then you might be fine just lumping them all in together). But you can reasonably put some of these studies together in groups. The most current systematic review on publication bias, from 2010, from which the examples above are taken, draws together the evidence from various fields.29 Twelve comparable studies follow up conference presentations, and taken together they find that a study with a significant finding is 1.62 times more likely to be published.
Why do negative trials disappear? In a moment we will see more clear cases of drug companies withholding data – in stories where we can identify individuals – sometimes with the assistance of regulators. When we get to these, I hope your rage might swell. But first, it’s worth taking a moment to recognise that publication bias occurs outside commercial drug development, and in completely unrelated fields of academia, where people are motivated only by reputation, and their own personal interests. In many respects, after all, publication bias is a very human process. If you’ve done a study and it didn’t have an exciting, positive result, then you might wrongly conclude that your experiment isn’t very interesting to other researchers. There’s also the issue of incentives: academics are often measured, rather unhelpfully, by crude metrics like the numbers of citations for their papers, and the number of ‘high-impact’ studies they get into glamorous well-read journals.
Bad Science by Ben Goldacre
Asperger Syndrome, correlation does not imply causation, experimental subject, hygiene hypothesis, Ignaz Semmelweis: hand washing, John Snow's cholera map, Louis Pasteur, meta analysis, meta-analysis, Nelson Mandela, offshore financial centre, p-value, placebo effect, publication bias, Richard Feynman, risk tolerance, Ronald Reagan, selection bias, selective serotonin reuptake inhibitor (SSRI), the scientific method, urban planning
If there is no publication bias, you should see a nice inverted funnel: the big, accurate trials all cluster around each other at the top of the funnel, and then as you go down the funnel, the little, inaccurate trials gradually spread out to the left and right, as they become more and more wildly inaccurate—both positively and negatively. If there is publication bias, however, the results will be skewed. The smaller, more rubbish negative trials seem to be missing, because they were ignored—nobody had anything to lose by letting these tiny, unimpressive trials sit in their bottom drawer—and so only the positive ones were published. Not only has publication bias been demonstrated in many fields of medicine, but a paper has even found evidence of publication bias in studies of publication bias. Here is the funnel plot for that paper.
If you aim too high and get a few rejections, it could be years until your paper comes out, even if you are being diligent: that’s years of people not knowing about your study. Publication bias is common, and in some fields it is more rife than in others. In 1995, only 1 per cent of all articles published in alternative medicine journals gave a negative result. The most recent figure is 5 per cent negative. This is very, very low, although to be fair, it could be worse. A review in 1998 looked at the entire canon of Chinese medical research, and found that not one single negative trial had ever been published. Not one. You can see why I use CAM as a simple teaching tool for evidence-based medicine. Generally the influence of publication bias is more subtle, and you can get a hint that publication bias exists in a field by doing something very clever called a funnel plot. This requires, only briefly, that you pay attention.
But these, at least, were transparent flaws: you only had to read the trial to see that the researchers had given a miserly dose of a painkiller; and you should always read the methods and results section of a trial to decide what its findings are, because the discussion and conclusion pages at the end are like the comment pages in a newspaper. They’re not where you get your news from. How can we explain, then, the apparent fact that industry funded trials are so often so glowing? How can all the drugs simultaneously be better than all of the others? The crucial kludge may happen after the trial is finished. Publication bias and suppressing negative results ‘Publication bias’ is a very interesting and very human phenomenon. For a number of reasons, positive trials are more likely to get published than negative ones. It’s easy enough to understand, if you put yourself in the shoes of the researcher. Firstly, when you get a negative result, it feels as if it’s all been a bit of a waste of time. It’s easy to convince yourself that you found nothing, when in fact you discovered a very useful piece of information: that the thing you were testing doesn’t work.
I Think You'll Find It's a Bit More Complicated Than That by Ben Goldacre
call centre, conceptual framework, correlation does not imply causation, crowdsourcing, death of newspapers, Desert Island Discs, en.wikipedia.org, experimental subject, Firefox, Flynn Effect, jimmy wales, John Snow's cholera map, Loebner Prize, meta analysis, meta-analysis, moral panic, placebo effect, publication bias, selection bias, selective serotonin reuptake inhibitor (SSRI), Simon Singh, statistical model, stem cell, the scientific method, Turing test, WikiLeaks
: First, Magnetise Your Wine What Is Science: http://www.badscience.net/2005/12/what-is-science-first-magnetise-your-wine/ BAD ACADEMIA What If Academics Were as Dumb as Quacks with Statistics What if Academics: http://www.badscience.net/2011/10/what-if-academics-were-as-dumb-as-quacks-with-statistics/ publish a mighty torpedo: http://www.nature.com/neuro/journal/v14/n9/full/nn.2886.html Brain-Imaging Studies Report More Positive Findings Than Their Numbers Can Support. This Is Fishy Brain-Imaging Studies: http://www.badscience.net/2011/08/brain-imaging-studies-report-more-positive-findings-than-their-numbers-can-support-this-is-fishy/ publication bias:http://www.badscience.net/category/publication-bias/ took a different approach: http://archpsyc.ama-assn.org/cgi/content/abstract/archgenpsychiatry.2011.28 ‘None of Your Damn Business’ None of Your: http://www.badscience.net/2011/01/none-of-your-damn-business/ 2004 published a study: http://ats.ctsnetjournals.org/cgi/content/abstract/annts;78/4/1433 it was retracted: http://retractionwatch.wordpress.com/2011/01/04/thoracic-surgery-journal-retracts-hypertension-study-marred-by-troubled-data/ Dr L.
You’ll have seen plenty of news stories telling you that one part of the brain is bigger, or smaller, in people with a particular mental health problem, or even a specific job. These are generally based on real, published scientific research. But how reliable are the studies? One way of critiquing a piece of research is to read the academic paper itself, in detail, looking for flaws. But that might not be enough, if some sources of bias might exist outside the paper, in the wider system of science. By now you’ll be familiar with publication bias: the phenomenon whereby studies with boring negative results are less likely to get written up, and less likely to get published. Normally you can estimate this using a tool such as, say, a funnel plot. The principle behind these is simple: big, expensive landmark studies are harder to brush under the carpet, but small studies can disappear more easily. So essentially you split your studies into ‘big ones’ and ‘small ones’: if the small studies, averaged out together, give a more positive result than the big studies, then maybe some small negative studies have gone missing in action.
By working backwards and sideways from these kinds of calculations, Ioannidis was able to determine, from the sizes of effects measured, and from the numbers of people scanned, how many positive findings could plausibly have been expected, and compare that to how many were actually reported. The answer was stark: even being generous, there were twice as many positive findings as you could realistically have expected from the amount of data reported on. What could explain this? Inadequate blinding is an issue: a fair amount of judgement goes into measuring the size of a brain area on a scan, so wishful nudges can creep in. And boring old publication bias is another: maybe whole negative papers aren’t getting published. But a final, more interesting explanation is also possible. In these kinds of studies, it’s possible that many brain areas are measured to see if they’re bigger or smaller, and maybe then only the positive findings get reported within each study. There is one final line of evidence to support this. In studies of depression, for example, thirty-one studies report data on the hippocampus, six on the putamen, and seven on the prefrontal cortex.
Statistics in a Nutshell by Sarah Boslaugh
Antoine Gombaud: Chevalier de Méré, Bayesian statistics, business climate, computer age, correlation coefficient, experimental subject, Florence Nightingale: pie chart, income per capita, iterative process, job satisfaction, labor-force participation, linear programming, longitudinal study, meta analysis, meta-analysis, p-value, pattern recognition, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, purchasing power parity, randomized controlled trial, selection bias, six sigma, statistical model, The Design of Experiments, the scientific method, Thomas Bayes, Vilfredo Pareto
Note also that this plot is basically symmetrical, indicating that a range of studies with positive, negative, and nonsignificant results has been published. A funnel plot with the general shape shown in Figure 20-1 suggests that publication bias is not a large concern in this particular area of research. A funnel plot that looks more like Figure 20-2 does suggest publication bias; about half of the funnel is missing because few studies have been published with a neutral or negative result. The plot alone does not prove publication bias (several other possibilities are discussed in the Cochrane Collaboration document listed in Appendix C), but it does suggest it as a possibility. Figure 20-1. A funnel plot suggesting little to no publication bias Figure 20-2. A funnel plot suggesting publication bias Issues in Research Design Generally, the design of an investigation of a question of interest needs to follow the guidelines presented in Chapter 18 if meaningful inferences are eventually to be made.
Failure to do so leads to publication bias, in which only significant results are published, creating a misleading picture of our state of knowledge. Don’t be afraid to report deviations, nonsignificant test results, and failure to reject null hypotheses—not every experiment can or should result in a major scientific result! Publication Bias and the Funnel Plot It’s easy to fall into the naïve belief that the published research literature presents a fair picture of our collective knowledge in any research field. If you do a proper literature search and find four research articles demonstrating the effectiveness of a particular drug and no articles saying it is ineffective, that’s pretty good evidence that the drug works, right? Unfortunately, not always. The reason is publication bias (also known as the file drawer problem), the tendency for articles presenting statistically significant results to be published and articles without such results to remain unpublished (and in the file drawer).
For instance, research published in English might be more readily available than equally good or better research published in other languages and thus more likely to be cited repeatedly by other articles. (The number of citations is sometimes used as a measure of an article’s importance or influence.) One way to evaluate publication bias on a topic is to create a funnel plot, a graph in which each data point represents a published study, with the log odds ratio of the study on the horizontal axis and the standard error of the study on the vertical axis. If there is no publication bias, we expect to see a pattern similar to an inverted funnel, as in Figure 20-1. Note that in studies with a larger standard error (less precise studies), there is a greater variability of results (a wider range of values for the log odds ratio), whereas for more precise studies, the log odds ratio clusters more closely around a single value.
The Art of Statistics: Learning From Data by David Spiegelhalter
Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Carmen Reinhart, complexity theory, computer vision, correlation coefficient, correlation does not imply causation, dark matter, Edmond Halley, Estimating the Reproducibility of Psychological Science, Hans Rosling, Kenneth Rogoff, meta analysis, meta-analysis, Nate Silver, Netflix Prize, p-value, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, randomized controlled trial, recommendation engine, replication crisis, self-driving car, speech recognition, statistical model, The Design of Experiments, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus
There is nothing in the paper that will reveal the total implausibily of this result – external knowledge is required.7 Publication Bias Scientists examine huge numbers of published articles when they are conducting systematic reviews – trying to bring together the literature and synthesize the current state of knowledge. Such an enterprise becomes hopelessly flawed if what is published is a biased subset of the work that has been carried out, say because negative results have not been submitted for publication, or questionable research practices have led to an unjustified excess of significant results. Statistical techniques have been developed for identifying such publication bias. Suppose we have a set of studies that all set out to test the same null hypothesis that an intervention has no effect.
Then this is just the pattern that would occur were the null hypothesis true, and the only results being reported as significant were those 1 in 20 that tipped over P < 0.05 by luck. Simonsohn and others looked at the published psychological literature which supported the popular idea that giving people an excessive amount of choice led to negative consequences; an analysis of the P-curve suggested there was substantial publication bias and that there was no good evidence for this effect.8 Assessing a Statistical Claim or Story Whether we are journalists, fact-checkers, academics, professionals in government or business or NGOs, or simply members of the public, we are regularly told claims that are based on statistical evidence. Assessing the trustworthiness of statistical claims appears a vital skill for the modern world.
Nelson and U. Simonsohn, ‘False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant’, Psychological Science 22:11 (November 2011), 1359–66. 7. A. Gelman and D. Weakliem, ‘Of Beauty, Sex and Power’, American Scientist 97:4 (2009), 310–16. 8. U. Simonsohn, L. D. Nelson and J. P. Simmons, ‘P-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results’, Perspectives on Psychological Science 9:6 (November 2014), 666–81. 9. For more on intelligent openness, see Royal Society, Science as an Open Enterprise (2012). Onora O’Neill’s perspectives on trustworthiness are brilliantly explained in her TedX talk ‘What We Don’t Understand About Trust’ (June 2013). 10. The methodology for the exit polls has been explained by David Firth at https://warwick.ac.uk/fac/sci/statistics/staff/academic-research/firth/exit-poll-explainer/.
Randomistas: How Radical Researchers Changed Our World by Andrew Leigh
Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, Atul Gawande, basic income, Black Swan, correlation does not imply causation, crowdsourcing, David Brooks, Donald Trump, ending welfare as we know it, Estimating the Reproducibility of Psychological Science, experimental economics, Flynn Effect, germ theory of disease, Ignaz Semmelweis: hand washing, Indoor air pollution, Isaac Newton, Kickstarter, longitudinal study, loss aversion, Lyft, Marshall McLuhan, meta analysis, meta-analysis, microcredit, Netflix Prize, nudge unit, offshore financial centre, p-value, placebo effect, price mechanism, publication bias, RAND corporation, randomized controlled trial, recommendation engine, Richard Feynman, ride hailing / ride sharing, Robert Metcalfe, Ronald Reagan, statistical model, Steven Pinker, uber lyft, universal basic income, War on Poverty
I confess that I’m one of those who is guilty of popularising it without reviewing the follow-up studies: Andrew Leigh, The Economics of Just About Everything, Sydney: Allen & Unwin, 2014, p. 10. 44Benjamin Scheibehenne, Rainer Greifeneder & Peter M. Todd, ‘Can there ever be too many options? A meta-analytic review of choice overload’, Journal of Consumer Research, vol. 37, no. 3, 2010, pp. 409–25. 45Alan Gerber & Neil Malhotra, ‘Publication bias in empirical sociological research’, Sociological Methods & Research, vol. 37, no. 1, 2008, pp. 3–30; Alan Gerber & Neil Malhotra, ‘Do statistical reporting standards affect what is published? Publication bias in two leading political science journals’, Quarterly Journal of Political Science. vol. 3, no. 3, 2008, pp. 313–26; E.J. Masicampo & Daniel R. Lalande, ‘A peculiar prevalence of p values just below .05’, Quarterly Journal of Experimental Psychology, vol. 65, no. 11, 2012, pp. 2271–9; Kewei Hou, Chen Xue & Lu Zhang, ‘Replicating anomalies’, NBER Working Paper 23394, Cambridge, MA: National Bureau of Economic Research, 2017. 46Alexander A.
Wherever a replication is conducted, it’s crucial that the results are reported. If researchers conceal findings that run counter to conventional wisdom, then the rest of us may form a mistaken impression of the results of available randomised trials. Like a golfer who takes a mulligan on every hole, discarded trials can leave us in a situation where the scorecard doesn’t reflect reality. One way of countering ‘publication bias’ is to require that studies be registered before they start – by lodging a statement in advance in which the researchers specify the questions they are seeking to answer. This makes it more likely that studies are reported after they finish. In medicine, there are fifteen major clinical trial registers around the world, including ones operated by Australia and New Zealand, China, the European Union, India, Japan, the Netherlands and Thailand.
Olds, David 211 ‘once and done’ campaign, and Smile Train aid charity 158 O’Neill, John, and Black Saturday 2009 13–14 O’Neill, Maura 210 Oportunidades Mexico 117 see also President Vincent Fox Oregon research on health insurance 42 parachute study, and randomised evaluation of 12 Pare, Ambroise, and soldiers’ gunpowder burns 22–3 parenting programs 68–9 and Chicago ‘Parent Academy’ 9 and Incredible Years Basic Parenting Programme 69 and randomised evaluations 70 ‘Triple P’ positive parenting program 68–9 ‘partial equilibrium’ effect 191 Peirce, Charles Sanders 49–51 Perry, Rick 150–1 Perry Preschool 66–8, 71, 169, 191–2 see also David Weikart; Evelyn Moore ‘P-hacking’ 195–6 Piaget, Jean 66 Pinker, Stephen 177 placebo effect 10, 29–31, 34, 138, 192 and John Haygarth 23–4 placebo surgery 18–21 see also sham surgery Planet Money 103 policing programs 91–4, 209 ‘broken windows policing’ 209 and ‘hot spots’ policing 93 and ‘problem oriented policing’ 94 and randomised evaluations 94 see also criminal justice experiments; Lawrence Sherman; Patrick Murphy; Rudi Lammers political campaign strategies and Benin political campaign 160 and control groups 148, 155 and ‘deep canvassing’ 163–4 and Harold Gosnell 148–50 and lobbying in US 162 and online campaigning 154–5 and political speeches 160–1 and ‘robocalls’ 152 and Sierra Leone election debates 161 and use of ‘social pressure’ 151–2 see also Get Out the Vote Pope Benedict XVI 119 ‘power of free’ theory 112 pragmatism 50 see also Charles Sanders Pierce ‘problem oriented policing’ 94 Programme for International Student Assessment 73 Progresa Mexico 117–18 see also President Ernesto Zedillo Project Independence 60–1 see also Ben Graber; Judith Gueron; Manpower Demonstration Research Corporation (MDRC) Project STAR experiment 81 Promise Academy 78–9 Prospera Mexico 118 psychology experiments 50–1, 143, 170, 177, 196 see also Charles Sanders Pierce; Joseph Jastrow ‘publication bias’ 199 Pyrotron 14–15 see also Andrew Sullivan Quintanar, Maricela 38–40 Quora 131 RAND Health Insurance Experiment 41, 169 randomised auditing 174–5 randomised trials see also A/B testing and ‘anchoring’ effect 133 and the book of Daniel 22 and Community Led Sanitation 116 and control groups 13, 67–8, 74, 78, 82 and data collection 171–2 and the driving licence experiment 109 and the ‘experimental idea’ 194 fairness of 37, 100, 177, 185 and ‘fixed mindset’ 6 and ‘general equilibrium’ effect 191 and the ‘gold standard’ 194 and ‘growth mindset’ 6 and ‘healthy cohort’ effect 12 and Highest Paid Person’s Opinion (HiPPO) 6 and Kenyan mini-bus driver experiments 115–16 and ‘natural experiments’ 193 and N-of-1 168–9 and the No Child Left Behind Act 210 and ‘the paradox of choice’ 195 and ‘partial equilibrium’ effect 191 and ‘publication bias’ 199 and replication of 90, 124, 195, 197–8 and sex education 119–20 and single-centre trials 197 and ‘virginity pledges’ in the US 46–7 randomistas, Angus Deaton Nobel laureate on 12 Read India 188 see also Rukmini Banerji Reagan, President Ronald 59, 151 Registry for International Development Impact Evaluations 199 replication 90, 195, 197–8 ‘restorative justice conferencing’ 84 restorative justice experiments 85–6, 182 Results for America 211 Rhinehart, Luke, and The Dice Man 180 Roach, William 52 ‘robocalls’ 152 Romney, Mitt 147 Rossi, Peter 190 ‘Rossi’s Law’ 190, 206 Rothamsted Experimental Centre 53 Rudder, Christian 130 see also OkCupid Sachs, Jeffrey 121 Sackett, David 27, 206 Sacred Heart Mission 36 Salk, Jonas 168 Salvation Army’s ‘Red Kettle Christmas drive 157 Sandburg, Sheryl 144 Saut, Fabiola Vasquez 110 see also Acayucan road experiment ‘scaling proven success,’ and ‘Development Innovation Ventures’ 210 Scared Straight 7–8, 94, 98–9, 189 see also Danny Glover; James Finckenauer Schmidt, Eric, and Google 143 Schwarzenegger, Arnold 75, 173 Science 163 ‘Science of Philanthropy Initiative’ 159 scurvy treatment trials 3–5, 16 see also Gilbert Blane; James Cook; James Lind; William Stark Second Chance Act 210 Seeger, Pete, and ‘The Draft Dodger Rag’ 42 Semelweiss, Ignaz 25 Sesame Street 63–5, 83 see also Joan Cooney sex education 119–20 sham surgery trials 19–20, 182 and ‘clinical equipoise’ 21 Sherman, Lawrence 91–4, 101 ‘Shoes for Better Tomorrows’ (TOMS) 113–15 see also Blake Mycoskie; Bruce Wydick Sierra Leone election debates 161 see also Saa Badabla SimCalc, and online learning tools 77 ‘single subject’ trials 168–9 see also N-of-1 Siroker, Dan 148 Sliding Doors 9 Smile Train aid charity, and ‘once and done’ campaign 158 social experiments large-scale 41 social field experiments and control groups 37, 39–41, 139 and credit card upgrades 132–3 and pay rates 136–7 and retail discounts 133 and ‘split cable’ techniques 139–40 and Western Union money transfers 130 social program trials and Kenyan electricity trial 110 and smoking deterrents 47–8 see also Acayucan road experiment; neighbourhood project social service agencies 36, 69 ‘soft targeting’ 36 ‘split cable’ technique 139–40 St.
Human Diversity: The Biology of Gender, Race, and Class by Charles Murray
23andMe, affirmative action, Albert Einstein, Alfred Russel Wallace, Asperger Syndrome, assortative mating, basic income, bioinformatics, Cass Sunstein, correlation coefficient, Daniel Kahneman / Amos Tversky, double helix, Drosophila, epigenetics, equal pay for equal work, European colonialism, feminist movement, glass ceiling, Gunnar Myrdal, income inequality, Kenneth Arrow, labor-force participation, longitudinal study, meta analysis, meta-analysis, out of africa, p-value, phenotype, publication bias, quantitative hedge fund, randomized controlled trial, replication crisis, Richard Thaler, risk tolerance, school vouchers, Scientific racism, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, social intelligence, statistical model, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, Thomas Kuhn: the structure of scientific revolutions, twin studies, universal basic income, working-age population
There are several indications that such decisions have been a problem with stereotype threat research: Replications often fail to confirm the earlier results. The evidence for stereotype threat has dissipated over time.37 Publication bias (failure to report negative results) appears to have been a reality. In 2019, scholars at the University of Minnesota dealt with these and other issues in the most comprehensive meta-analysis of stereotype threat to date, focusing on the high-stakes test settings in which stereotype threat should theoretically cause the most problems. For the studies relevant to high-stakes settings, the effect size of stereotype threat was –.14 (lowering test scores), a small effect that was further reduced to –.09 after correcting for publication bias. The authors summarized their findings as follows: Based on the results of the focal analysis, operational and motivational subsets, and publication bias analyses, we conclude that the burden of proof shifts back to those that claim that stereotype threat exerts a substantial effect on standardized test takers.
Because so much of the controversy involves abstruse psychometric issues, I take his conclusion seriously: To conclude, we estimated a small average effect of stereotype threat on the MSSS [math, science, and spatial skills] test-performance of school-aged girls [d = –0.22]; however, the studies show large variation in outcomes, and it is likely that the effect is inflated due to publication bias. This finding leads us to conclude that we should be cautious when interpreting the effects of stereotype threat on children and adolescents in the STEM realm. To be more explicit, based on the small average effect size in our meta-analysis, which is most likely inflated due to publication bias, we would not feel confident to proclaim that stereotype threat manipulations will harm mathematical performance of girls in a systematic way or lead women to stay clear from occupations in the STEM domain. (Flore and Wicherts (2015): 41). 39.
Author: Nguyen and Ryan (2008) Effect size (d): –0.21 Author: Stoet and Geary (2012) Effect size (d): –0.17 Author: Picho et al. (2013) Effect size (d): –0.24 Author: Flore and Wicherts (2015) Effect size (d): –0.22 Author: Doyle and Voyer (2016) Effect size (d): –0.29 Given how closely the effect sizes are grouped, it is bemusing to read the authors’ perspectives on whether the glass is half full or half empty. The authors of three of the studies treat their effect sizes more or less at face value and think they have practical implications (Nguyen and Ryan, Picho et al., Doyle and Voyer). In contrast, Stoet and Geary and Flore and Wicherts are both worried about the degree to which there is evidence of publication bias (only studies that find stereotype threat reach publication), a lack of control groups in many studies, and other methodological weaknesses. The studies of race-based stereotype threat do not have an equivalent body of meta-analytic results, in large part because of the difficulty of assembling large sample sizes. The Nguyen and Ryan meta-analysis reported an effect size for ethnic minorities of –0.32. Psychologists Gregory Walton and Steven Spencer combined three field studies using African American participants to test race-based stereotype threat.
The Half-Life of Facts: Why Everything We Know Has an Expiration Date by Samuel Arbesman
Albert Einstein, Alfred Russel Wallace, Amazon Mechanical Turk, Andrew Wiles, bioinformatics, British Empire, Cesare Marchetti: Marchetti’s constant, Chelsea Manning, Clayton Christensen, cognitive bias, cognitive dissonance, conceptual framework, David Brooks, demographic transition, double entry bookkeeping, double helix, Galaxy Zoo, guest worker program, Gödel, Escher, Bach, Ignaz Semmelweis: hand washing, index fund, invention of movable type, Isaac Newton, John Harrison: Longitude, Kevin Kelly, life extension, Marc Andreessen, meta analysis, meta-analysis, Milgram experiment, Nicholas Carr, P = NP, p-value, Paul Erdős, Pluto: dwarf planet, publication bias, randomized controlled trial, Richard Feynman, Rodney Brooks, scientific worldview, social graph, social web, text mining, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Tyler Cowen: Great Stagnation
While some have made this out to be somewhat mysterious, that needn’t always be the case, as shown in the example of Planet X. Increasingly precise measurement allows us to often be more accurate in what we are looking for. And these improvements frequently dial the effects downward. But the decline effect is not only due to measurement. One other factor involves the dissemination of measurements, and it is known as publication bias. Publication bias is the idea that the collective scientific community and the community at large only know what has been published. If there is any sort of systematic bias in what is being published (and therefore publicly measured), then we might only be seeing some of the picture. The clearest example of this is in the world of negative results. If you recall, John Maynard Smith noted that “statistics is the science that lets you do twenty experiments a year and publish one false result in Nature.”
., 174 Godwin’s law, 105 Goldbach’s Conjecture, 112–13 Goodman, Steven, 107–8 Gould, Stephen Jay, 82 grammar: descriptive, 188–89 prescriptive, 188–89, 194 Granovetter, Mark, 76–78 Graves’ disease, 111 Great Vowel Shift, 191–93 Green, George, 105–6 growth: exponential, 10–14, 44–45, 46–47, 54–55, 57, 59, 130, 204 hyperbolic, 59 linear, 10, 11 Gumbel, Bryant, 41 Gutenberg, Johannes, 71–73, 78, 95 Hamblin, Terry, 83 Harrison, John, 102 Hawthorne effect, 55–56 helium, 104 Helmann, John, 162 Henrich, Joseph, 58 hepatitis, 28–30 hidden knowledge, 96–120 h-index, 17 Hirsch, Jorge, 17 History of the Modern Fact, A (Poovey), 200 Holmes, Sherlock, 206 homeoteleuton, 89 Hooke, Robert, 21, 94 Hull, David, 187–88 human anatomy, 23 human computation, 20 hydrogen, 151 hyperbolic growth rate, 59 idiolect, 190 impact factors, 16–17 inattentional blindness (change blindness), 177–79 India, 140–41 informational index funds, 197 information transformation, 43–44, 46 InnoCentive, 96–98, 101, 102 innovation, 204 population size and, 135–37, 202 prizes for, 102–3 simultaneous, 104–5 integrated circuits, 42, 43, 55, 203 Intel Corporation, 42 interdisciplinary research, 68–69 International Bureau of Weights and Measures, 47 Internet, 2, 40–41, 53, 198, 208, 211 Ioannidis, John, 156–61, 162 iPhone, 123 iron: magnetic properties of, 49–50 in spinach, 83–84 Ising, Ernst, 124, 125–26, 138 isotopes, 151 Jackson, John Hughlings, 30 Johnson, Steven, 119 Journal of Physical and Chemical Reference Data, 33–35 journals, 9, 12, 16–17, 32 Kahneman, Daniel, 177 Kay, Alan, 173 Kelly, Kevin, 38, 46 Kelly, Stuart, 115 Kelvin, Lord, 142–43 Kennaway, Kristian, 86 Keynes, John Maynard, 172 kidney stones, 52 kilogram, 147–48 Kiribati, 203 Kissinger, Henry, 190 Kleinberg, Jon, 92–93 knowledge and facts, 5, 54 cumulative, 56–57 erroneous, 78–95, 211–14 half-lives of, 1–8, 202 hidden, 96–120 phase transitions in, 121–39, 185 spread of, 66–95 Koh, Heebyung, 43, 45–46, 56 Kremer, Michael, 58–61 Kuhn, Thomas, 163, 186 Lambton, William, 140 land bridges, 57, 59–60 language, 188–94 French Canadians and, 193–94 grammar and, 188–89, 194 Great Vowel Shift and, 191–93 idiolect and, 190 situation-based dialect and, 190 verbs in, 189 voice onset time and, 190 Large Hadron Collider, 159 Laughlin, Gregory, 129–31 “Laws Underlying the Physics of Everyday Life Really Are Completely Understood, The” (Carroll), 36–37 Lazarus taxa, 27–28 Le Fanu, James, 23 LEGO, 184–85, 194 Lehman, Harvey, 13–14, 15 Leibniz, Gottfried, 67 Lenat, Doug, 112 Levan, Albert, 1–2 Liben-Nowell, David, 92–93 libraries, 31–32 life span, 53–54 Lincoln, Abraham, 70 linear growth, 10, 11 Linnaeus, Carl, 22, 204 Lippincott, Sara, 86 Lipson, Hod, 113 Little Science, Big Science (Price), 13 logistic curves, 44–46, 50, 116, 130, 203–4 longitude, 102 Long Now Foundation, 195 long tails: of discovery, 38 of expertise, 96, 102 of life, 38 of popularity, 103 Lou Gehrig’s disease (ALS), 98, 100–101 machine intelligence, 207 Magee, Chris, 43, 45–46, 56, 207–8 magicians, 178–79 magnetic properties of iron, 49–50 Maldives, 203 Malthus, Thomas, 59 mammal species, 22, 23, 128 extinct, 28 manuscripts, 87–91, 114–16 Marchetti, Cesare, 64 Marsh, Othniel, 80–81, 169 mathematics, 19, 51, 112–14, 124–25, 132–35 Matthew effect, 103 Mauboussin, Michael, 84 Mayor, Michel, 122 McGovern, George, 66 McIntosh, J. S., 81–82 McWhorter, John, 191 measurement, 142–70 decline effect and, 155–56, 157 kilogram in, 147–48 meter in, 143–47 of Mount Everest, 140–41 precision and accuracy in, 149–50 prefixes in, 47–48, 142, 147 publication bias and, 156 of trees, 142 Mechanical Turk, 180–82 medical knowledge, 23, 32, 51–52, 53, 122, 197, 198, 208 about cirrhosis and hepatitis, 28–30 MEDLINE, 99–100 memorization, 198 Mendel, Gregor, 106 Mendeley, 117, 118 Merton, Robert, 61, 103, 104 mesofacts, 6–7, 195, 203 meta-analysis, 107–8 cumulative, 109–10 meter, 143–47 Milgram, Stanley, 24, 167 mobile phone calls, 69, 77 Moon, 2, 126–28, 129, 138, 174, 203 Moore, Gordon, 42, 55, 56 Moore’s Law, 41–43, 46, 48, 51, 55, 56, 64, 203 Moriarty, James, 85–86 Mount Everest, 140–41 Mueller, John, 165 Munroe, Randall, 84, 153–54 Murphy, Tom, 55 mutation, 87–94 Napier’s constant, 12 National Institutes of Health, 17 natural selection, 104–5, 187 Nature, 122, 154, 156, 162, 166 negative results, 162 Neptune, 154–55, 183 network science, 74–78 neuroscience, 48 New Scientist, 85 Newton, Isaac, 21, 36, 67, 94, 174, 186 New Yorker, 86 New York Times, 20, 75, 174 Nobel laureates, 18 nosebleeds, 180–82 Noyce, Robert, 42 null hypothesis, 152 Obama, Barack, 179 Oliver, John, 159 Onnela, Jukka-Pekka, 69, 77 On the Origin of Species (Darwin), 79, 187 opera, 14–15 orders, 60 Original Theory or New Hypothesis of the Universe, An (Wright), 121–22 Pacioli, Luca, 200 paleography, 87–90 paradigm, 186 paradigm shift, 186, 187 Parmentier, Antoine, 102 particle accelerator, 51 Patent Office, 54 Pauly, Daniel, 172–73 Pepys, Samuel, 52 periodic table, 50, 150–52, 182 Petroski, Henry, 49 phase transitions, 207 in acceptance and assimilation of knowledge, 185, 186 in facts, 121–39, 185 Ising model and, 124, 125–26, 138 in physics, 123–24, 126 Philosophical Transactions of the Royal Society of London, 9, 12 physics, 32 Planck, Max, 186–88 planets, 6, 121–23, 128, 129–31, 132, 183–84 Planet X, 154–56, 160 Pluto, 122–23, 128, 138, 148–49, 155, 183–84 polio, 52 Pony Express, 70 Poovey, Mary, 200 Popeye the Sailor, 83, 213 population: innovation and, 135–37, 202 makeup of, 61 size of, 2, 6, 57–61, 122, 135–37, 204 Portugal, 207 posterior probability, 159 potatoes, 102 preferential attachment, 103 prefixes, 47–48, 142, 147 Price, Derek J. de Solla, 9, 12–13, 15, 17, 32, 47, 50, 103, 166–67 prices, 196–97 printing press, 70–74, 78, 115 prior probability, 159 Pritchett, Lant, 186 Prize4Life Foundation, 97–98 productivity, 55–56 programmed cell death, 111, 194 proteomics, 48 Proteus phenomenon, 161 publication bias, 156 p-values, 152–54, 156, 158 P versus NP, 133–35 “Quantitative Measures of the Development of Science” (Price), 12 Quebec, 193–94 Queloz, Didier, 122 radioactivity, 2–3, 29, 33 Raynaud’s syndrome, 99, 110 reading, 197–98 Real Time Statistics Project, 195 reinventions, 104–5 Rendezvous with Rama (Clarke), 19 Rényi, Alfréd, 104 replication, 161–62 Riggs, Elmer, 81 Robinson, Karen, 107–8 robots, 46 Royal Society, 94–95 Roychowdhury, Vwani, 91, 103–4 Russell, C.
., 81–82 McWhorter, John, 191 measurement, 142–70 decline effect and, 155–56, 157 kilogram in, 147–48 meter in, 143–47 of Mount Everest, 140–41 precision and accuracy in, 149–50 prefixes in, 47–48, 142, 147 publication bias and, 156 of trees, 142 Mechanical Turk, 180–82 medical knowledge, 23, 32, 51–52, 53, 122, 197, 198, 208 about cirrhosis and hepatitis, 28–30 MEDLINE, 99–100 memorization, 198 Mendel, Gregor, 106 Mendeley, 117, 118 Merton, Robert, 61, 103, 104 mesofacts, 6–7, 195, 203 meta-analysis, 107–8 cumulative, 109–10 meter, 143–47 Milgram, Stanley, 24, 167 mobile phone calls, 69, 77 Moon, 2, 126–28, 129, 138, 174, 203 Moore, Gordon, 42, 55, 56 Moore’s Law, 41–43, 46, 48, 51, 55, 56, 64, 203 Moriarty, James, 85–86 Mount Everest, 140–41 Mueller, John, 165 Munroe, Randall, 84, 153–54 Murphy, Tom, 55 mutation, 87–94 Napier’s constant, 12 National Institutes of Health, 17 natural selection, 104–5, 187 Nature, 122, 154, 156, 162, 166 negative results, 162 Neptune, 154–55, 183 network science, 74–78 neuroscience, 48 New Scientist, 85 Newton, Isaac, 21, 36, 67, 94, 174, 186 New Yorker, 86 New York Times, 20, 75, 174 Nobel laureates, 18 nosebleeds, 180–82 Noyce, Robert, 42 null hypothesis, 152 Obama, Barack, 179 Oliver, John, 159 Onnela, Jukka-Pekka, 69, 77 On the Origin of Species (Darwin), 79, 187 opera, 14–15 orders, 60 Original Theory or New Hypothesis of the Universe, An (Wright), 121–22 Pacioli, Luca, 200 paleography, 87–90 paradigm, 186 paradigm shift, 186, 187 Parmentier, Antoine, 102 particle accelerator, 51 Patent Office, 54 Pauly, Daniel, 172–73 Pepys, Samuel, 52 periodic table, 50, 150–52, 182 Petroski, Henry, 49 phase transitions, 207 in acceptance and assimilation of knowledge, 185, 186 in facts, 121–39, 185 Ising model and, 124, 125–26, 138 in physics, 123–24, 126 Philosophical Transactions of the Royal Society of London, 9, 12 physics, 32 Planck, Max, 186–88 planets, 6, 121–23, 128, 129–31, 132, 183–84 Planet X, 154–56, 160 Pluto, 122–23, 128, 138, 148–49, 155, 183–84 polio, 52 Pony Express, 70 Poovey, Mary, 200 Popeye the Sailor, 83, 213 population: innovation and, 135–37, 202 makeup of, 61 size of, 2, 6, 57–61, 122, 135–37, 204 Portugal, 207 posterior probability, 159 potatoes, 102 preferential attachment, 103 prefixes, 47–48, 142, 147 Price, Derek J. de Solla, 9, 12–13, 15, 17, 32, 47, 50, 103, 166–67 prices, 196–97 printing press, 70–74, 78, 115 prior probability, 159 Pritchett, Lant, 186 Prize4Life Foundation, 97–98 productivity, 55–56 programmed cell death, 111, 194 proteomics, 48 Proteus phenomenon, 161 publication bias, 156 p-values, 152–54, 156, 158 P versus NP, 133–35 “Quantitative Measures of the Development of Science” (Price), 12 Quebec, 193–94 Queloz, Didier, 122 radioactivity, 2–3, 29, 33 Raynaud’s syndrome, 99, 110 reading, 197–98 Real Time Statistics Project, 195 reinventions, 104–5 Rendezvous with Rama (Clarke), 19 Rényi, Alfréd, 104 replication, 161–62 Riggs, Elmer, 81 Robinson, Karen, 107–8 robots, 46 Royal Society, 94–95 Roychowdhury, Vwani, 91, 103–4 Russell, C.
Lost Connections: Uncovering the Real Causes of Depression – and the Unexpected Solutions by Johann Hari
basic income, Berlin Wall, call centre, correlation does not imply causation, Donald Trump, gig economy, income inequality, Jeff Bezos, John Snow's cholera map, Joi Ito, longitudinal study, meta analysis, meta-analysis, Naomi Klein, Occupy movement, open borders, placebo effect, precariat, publication bias, randomized controlled trial, Rat Park, risk tolerance, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), the scientific method, The Spirit Level, twin studies, universal basic income, urban planning, zero-sum game
., “Calculations are correct: reconsidering Fountoulakis & Möller’s re-analysis of the Kirsch data,” International Journal of Neuropsychopharmacology 15, no. 8 (August 2012): 1193–1198, doi: https://doi.org/10.1017/S1461145711001878; Erik Turner et al., “Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy,” N Engl J Med 358 (2008): 252–260, doi: 10.1056/NEJMsa065779. This is called “publication bias.” Evans, Emperor’s New Drugs, 25. My friend Dr. Ben Goldacre has done outstanding work on publication bias. See http://www.badscience.net/category/publication-bias/ for some background. Intrigued, Irving joined Evans, Emperor’s New Drugs, 26–7. Those twenty-seven patients Ibid., 41. “dirty little secret” Ibid., 38. In the end, in court, Ibid., 40; http://web.law.columbia.edu/sites/default/files/microsites/career-services/Driven%20to%20Settle.pdf; http://www.independent.co.uk/news/business/news/drug-firm-settles-seroxat-research-claim-557943.html; http://news.bbc.co.uk/1/hi/business/3631448.stm; http://www.pharmatimes.com/news/gsk_to_pay_$14m_to_settle_paxil_fraud_claims_995307; http://www.nbcnews.com/id/5120989/ns/business-us_business/t/spitzer-sues-glaxosmithkline-over-paxil/; http://study329.org/; http://science.sciencemag.org/content/304/5677/1576.full?
The vast majority of research into whether drugs work or not is funded by big pharmaceutical companies, and they do this research for a specific reason: they want to be able to market those drugs so they can make a profit out of them. That’s why the drug companies conduct their scientific studies in secret, and afterward, they only publish the results that make their drugs look good, or that make their rivals’ drugs look worse. They do this for exactly the same reasons that (say) KFC would never release information telling you that fried chicken isn’t good for you. This is called “publication bias.”7 Of all the studies drug companies carry out, 40 percent are never released to the public, and lots more are only released selectively, with any negative findings left on the cutting room floor. So, this e-mail explained to Irving, you have, up to now, been looking only at the parts of the scientific studies that the drug companies want us to see. But Thomas Moore said there is a way beyond this.
See psychedelic drugs psychedelic drugs effect of, here percentage of unpleasant experiences, here psychedelic drugs, spiritual experiences caused by 1950s-60s research on, here as escape from ego, here, here, here life-changing effects, here meditation as means of preserving effects of, here Roland’s experiments on, here sense of connection to others following, here, here, here similarity to meditation experience, here, here as treatment for depression, here, here, here psychiatrists and confusion of grief with depression, here focus on biological component of depression, here psychological causes of depression broad range of, here as too often ignored, here See also bio-psycho-social model of depression psychological changes as treatment for depression meditation and, here types of, here See also reconnecting strategies psychotherapy, as treatment for depression, here publication bias, in drug testing for antidepressant, here public engagement as treatment for depression, Kotti neighborhood protest and, here, here, here, here Putnam, Robert, here reactive model of depression vs. endogenous theory, here, here, here impact of research on, here, here research supporting, here, here reconnecting strategies, here author’s successful use of, here large changes required for, here, here as social/psychological antidepressant, here time and confidence needed to implement, here, here See also childhood trauma, overcoming; future, restoring; natural world, reconnection to; people, reconnection to; self/ego, overcoming addiction to; social prescribing; status and respect, reconnection to; values, meaningful, reconnecting to; work, reconnecting to relationships, extrinsic motivations and, here reSTART Life Internet addiction center, here, here Richards, Bill, here, here, here Rumspringa, here Ryan, Richard, here São Paulo, Brazil, banning of outdoor advertising, here Sapirstein, Guy analysis of antidepressant drug testing, here responses to drug testing analysis, here Sapolsky, Robert on genetic factors in depression, here recurring dream of, here research on baboon status hierarchies, here on stress of low or insecure status, here Schwenke, Regina, here Selective Serotonin Reuptake Inhibitors (SSRIs) and chemical imbalance model of depression, here, here effect of, as short-lived, here side effects of, here tests on effectiveness of, here self/ego effect of intrinsic vs. extrinsic motivation on, here experience of nature as escape from, here, here individual as prisoner of, in depression, here as protective barrier, here psychedelic drug experience as escape from, here, here, here resistance to diminishment of in some people, here Western vs.
How to Read a Paper: The Basics of Evidence-Based Medicine by Trisha Greenhalgh
call centre, complexity theory, conceptual framework, correlation coefficient, correlation does not imply causation, deskilling, knowledge worker, longitudinal study, meta analysis, meta-analysis, microbiome, New Journalism, p-value, personalized medicine, placebo effect, publication bias, randomized controlled trial, selection bias, the scientific method
Remember, too, that the results of an RCT may have limited applicability as a result of exclusion criteria (rules about who may not be entered into the study), inclusion bias (selection of trial participants from a group that is unrepresentative of everyone with the condition (see section ‘Whom is the study about?’)), refusal (or inability) of certain patient groups to give consent to be included in the trial, analysis of only pre-defined ‘objective’ endpoints which may exclude important qualitative aspects of the intervention (see Chapter 12) and publication bias (i.e. the selective publication of positive results, often but not always because the organisation that funded the research stands to gain or lose depending on the findings  ). Furthermore, RCTs can be well or badly managed , and, once published, their results are open to distortion by an over-enthusiastic scientific community or by a public eager for a new wonder drug . While all these problems might also occur with other trial designs, they may be particularly pertinent when an RCT is being sold to you as, methodologically speaking, whiter than white.
The authors report a series of artificial dice-rolling experiments in which red, white and green dice, respectively, represented different therapies for acute stroke. Overall, the ‘trials’ showed no significant benefit from the three therapies. However, the simulation of a number of perfectly plausible events in the process of meta-analysis—such as the exclusion of several of the ‘negative’ trials through publication bias (see section ‘Randomised controlled trials’), a subgroup analysis that excluded data on red dice therapy (because, on looking back at the results, red dice appeared to be harmful), and other, essentially arbitrary, exclusions on the grounds of ‘methodological quality’—led to an apparently highly significant benefit of ‘dice therapy’ in acute stroke. You cannot, of course, cure anyone of a stroke by rolling a dice, but if these simulated results pertained to a genuine medical controversy (such as which postmenopausal women would be best advised to take hormone replacement therapy or whether breech babies should routinely be delivered by Caesarean section), how would you spot these subtle biases?
Eysenck's reservations about meta-analysis are borne out in the infamously discredited meta-analysis that demonstrated (wrongly) that there was significant benefit to be had from giving intravenous magnesium to heart attack victims. A subsequent megatrial involving 58 000 patients (ISIS-4) failed to find any benefit whatsoever, and the meta-analysts' misleading conclusions were subsequently explained in terms of publication bias, methodological weaknesses in the smaller trials and clinical heterogeneity  . (Incidentally, for more debate on the pros and cons of meta-analysis versus megatrials, see this recent paper .) Eysenck's mathematical naiveté is embarrassing (‘if a medical treatment has an effect so recondite and obscure as to require a meta-analysis to establish it, I would not be happy to have it used on me’), which is perhaps why the editors of the second edition of the ‘Systematic reviews’ book dropped his chapter from their collection.
Everydata: The Misinformation Hidden in the Little Data You Consume Every Day by John H. Johnson
Affordable Care Act / Obamacare, Black Swan, business intelligence, Carmen Reinhart, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, Donald Trump, en.wikipedia.org, Kenneth Rogoff, labor-force participation, lake wobegon effect, Long Term Capital Management, Mercator projection, Mercator projection distort size, especially Greenland and Africa, meta analysis, meta-analysis, Nate Silver, obamacare, p-value, PageRank, pattern recognition, publication bias, QR code, randomized controlled trial, risk-adjusted returns, Ronald Reagan, selection bias, statistical model, The Signal and the Noise by Nate Silver, Thomas Bayes, Tim Cook: Apple, wikimedia commons, Yogi Berra
“P-hacking” (named after p-values) is a term used when researchers “collect or select data or statistical analyses until nonsignificant results become significant,” according to a PLoS Biology article.”36 This is similar to cherry picking, as p-hacking researchers simply throw things at the wall until something sticks, metaphorically speaking (although there probably are some scientists who actually throw things at the wall until something sticks…). A fascinating New Yorker article (is there any other kind?) examines publication bias as a possible cause of the “decline effect,” in which the size of a statistically significant effect declines over time. Why? One statistician found that “ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for,” making it perhaps less likely that future studies would be able to replicate these results.37 The Journal of Epidemiology and Community Health published a paper finding no evidence that reduced street lighting at night increased traffic collisions or crime in England and Wales.
See also misrepresentation and misinterpretation brain’s hardwiring for, 60–61 challenges in, 54–55 Ioannidis, John, 75 iPhones, 46–48, 58 “Ipse dixit” bias, 94 J Japan earthquake of 2011, 123–125 Jordan, Michael, 53 Journal of Epidemiology and Community Health, 80 Journal of Finance, 139–140 Journal of Safety Research, 20 Journal of the American Medical Informatics Association, 148 Journal of the National Cancer Institute, 69–70 K Katz, David, 22 Keillor, Garrison, 43 L Lake Wobegon effect, 42–43 Landon, Alfred, 132 Law360, 146–148 Lawyer Satisfaction Survey, 146–148 Literary Digest, 132 longevity, 4, 87–92 Los Angeles Times, 17–18 Lotto Stats, 133 Lund, Bob, 10 M magnitude, 77–78, 81 in birth month and health study, 149 map projections, 83–85 margins of error, 38, 68–69 Marie Claire, 34–35 math mistakes, 101–102, 103 mayors/deputy mayors salaries, 35–36 McCarthy, Jenny, 61 McGwire, Mark, 39 meaning, difficulty of extracting from too much data, 4. See also misrepresentation and misinterpretation means, 32–34 definition of, 32 mean trimming, 40 media cherry-picking by, 116 data interpretation by, 75, 81 publication bias and, 80 medians, 32–34 definition of, 32 medical coding errors, 97 Medical News Today, 75 memory of printed vs. online material, 2 Mercator, Gerardus, 83–85 misrepresentation and misinterpretation, 83–103. See also cherry-picking in charts, 87–92 correlation/causation based on, 58–60 data sources and, 99 errors and, 97–99 of food expiration dates, 99–100 in gas tank gauges, 96–97 guessing and, 86 helpful, 96–97 how to be a smart consumer and, 102–103 math mistakes and, 101–102 in the media, 75, 81 “only” and, 95–96 from treating all data equally, 95 trust in expertise and, 93–94 with visuals, 92–94 models, forecasts based on, 125–127 modes, 32–34 definition of, 32 Moore, Michael, 116 Morton Thiokol, 10 Moz.com, 55 multiple comparison problem, 75–76 N National Bureau of Economic Research, 59, 69 National Cancer Institute, 69–70 National Electronic Injury Surveillance System (NEISS), 18 National Foundation for Celiac Awareness, 21 National Weight Control Registry (NWCR), 17 Natural Resources Defense Council, 100 Nest, 100–101 Newman, Mark, 28–29 New York State Office of the Attorney General, 97 New York Times, 66–67 New York Times Magazine, 101 Nielsen, Arthur, Sr., 25 Nike, 53 NPD Group, 21 NWEA Measures of Academic Progress (MAP), 22–23 O Obama, Barack, 23, 27–30 observations, definition of, 13.
., 58, 76, 135 presidential campaigns/elections averages/aggregates and, 27–30, 44 cherry-picking in, 115–116 forecasting, 132, 137 polls and, 37–38, 68–69, 73 sampling and, 20 terms of office and, 41 Princeton Review of schools, 19 printed material vs. online differences in consumption/interpretation of, 7 willingness to question, 93–94 printed vs. online material memory of, 2 probability, 70–71, 81 coincidence and, 138–139 forecasting and, 131 proxies, 49–50 psychology research, 15–16 publication bias, 80 p-values, 71, 72, 79 Q questions/questioning, 7–8 cherry-picking and, 122 correlation vs. causation, 60 of print vs. online information, 93–94 quote mining, 116 R Radio Television Digital News Association, 36 random chance, multiple comparison problem and, 75–76, 80–81 random samples, 65–68 Rate My Professor, 51–52 Reagan, Ronald, 9 recall of printed vs. online material, 2 Reinhart, Carmen, 97–98 relationships, 5–6.
Getting Back to Full Employment: A Better Bargain for Working People by Dean Baker, Jared Bernstein
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, Asian financial crisis, business cycle, collective bargaining, declining real wages, full employment, George Akerlof, income inequality, inflation targeting, mass immigration, minimum wage unemployment, new economy, price stability, publication bias, quantitative easing, Report Card for America’s Infrastructure, rising living standards, selection bias, War on Poverty
While there are plenty of examples of countries that have maintained healthy growth rates even with double-digit inflation rates, it is fair to say that such rates raise a qualitatively different set of questions than the inflation rates that may arise from having an unemployment rate that is 0.5 to 1.0 percentage points below the level that is consistent with stable inflation for a period of time.  In fairness to advocates of inflation targeting, there is a wide range of views as to how strictly we should hold to the target as the primary or only goal of monetary policy.  There is also the possibility of publication bias. Given the strong belief by many economists that inflation reduces growth, there may be a reluctance to publish articles that find either insignificant results or even a positive relationship. This sort of publication bias was noted in the case of the minimum wage, where the distribution of published results has an otherwise inexplicable break at zero. If we assume that study results are normally distributed, there should be some number of studies that find a significant positive relationship between higher minimum wages and employment even if the true coefficient for an employment variable is zero (Doucouliagos and Stanley 2009)
Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann
affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Gödel, Escher, Bach, hindsight bias, housing crisis, Ignaz Semmelweis: hand washing, illegal immigration, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, lateral thinking, loss aversion, Louis Pasteur, Lyft, mail merge, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nuclear winter, offshore financial centre, p-value, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, survivorship bias, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, Vilfredo Pareto, wikimedia commons
If this type of data dredging happens routinely enough, then you can see why a large number of studies in the set to be replicated might have been originally false positives. In other words, in this set of one hundred studies, the base rate of false positives is likely much larger than 5 percent, and so another large part of the replication crisis can likely be explained as a base rate fallacy. Unfortunately, studies are much, much more likely to be published if they show statistically significant results, which causes publication bias. Studies that fail to find statistically significant results are still scientifically meaningful, but both researchers and publications have a bias against them for a variety of reasons. For example, there are only so many pages in a publication, and given the choice, publications would rather publish studies with significant findings over ones with none. That’s because successful studies are more likely to attract attention from media and other researchers.
There are advantages to meta-analyses, as combining data from multiple studies can increase the precision and accuracy of estimates, but they also have their drawbacks. For example, it is problematic to combine data across studies where the designs or sample populations vary too much. They also cannot eliminate biases from the original studies themselves. Further, both systematic reviews and meta-analyses can be compromised by publication bias because they can include only results that are publicly available. Whenever we are looking at the validity of a claim, we first look to see whether a thorough systematic review has been conducted, and if so, we start there. After all, systematic reviews and meta-analyses are commonly used by policy makers in decision making, e.g., in developing medical guidelines. If one thing is clear from this chapter, it’s probably that designing good experiments is tough!
., 38 oil, 105–6 Olympics, 209, 246–48, 285 O’Neal, Shaquille, 246 one-hundred-year floods, 192 Onion, 211–12 On the Origin of Species by Means of Natural Selection (Darwin), 100 OODA loop, 294–95 openness to experience, 250 Operation Ceasefire, 232 opinion, diversity of, 205, 206 opioids, 36 opportunity cost, 76–77, 80, 83, 179, 182, 188, 305 of capital, 77, 179, 182 optimistic probability bias, 33 optimization, premature, 7 optimums, local and global, 195–96 optionality, preserving, 58–59 Oracle, 231, 291, 299 order, 124 balance between chaos and, 128 organizations: culture in, 107–8, 113, 273–80, 293 size and growth of, 278–79 teams in, see teams ostrich with its head in the sand, 55 out-group bias, 127 outliers, 148 Outliers (Gladwell), 261 overfitting, 10–11 overwork, 82 Paine, Thomas, 221–22 pain relievers, 36, 137 Pampered Chef, 217 Pangea, 24–25 paradigm shift, 24, 289 paradox of choice, 62–63 parallel processing, 96 paranoia, 308, 309, 311 Pareto, Vilfredo, 80 Pareto principle, 80–81 Pariser, Eli, 17 Parkinson, Cyril, 74–75, 89 Parkinson’s law, 89 Parkinson’s Law (Parkinson), 74–75 Parkinson’s law of triviality, 74, 89 passwords, 94, 97 past, 201, 271–72, 309–10 Pasteur, Louis, 26 path dependence, 57–59, 194 path of least resistance, 88 Patton, Bruce, 19 Pauling, Linus, 220 payoff matrix, 212–15, 238 PayPal, 72, 291, 296 peak, 105, 106, 112 peak oil, 105 Penny, Jonathon, 52 pent-up energy, 112 perfect, 89–90 as enemy of the good, 61, 89–90 personality traits, 249–50 person-month, 279 perspective, 11 persuasion, see influence models perverse incentives, 50–51, 54 Peter, Laurence, 256 Peter principle, 256, 257 Peterson, Tom, 108–9 Petrified Forest National Park, 217–18 Pew Research, 53 p-hacking, 169, 172 phishing, 97 phones, 116–17, 290 photography, 302–3, 308–10 physics, x, 114, 194, 293 quantum, 200–201 pick your battles, 238 Pinker, Steven, 144 Pirahã, x Pitbull, 36 pivoting, 295–96, 298–301, 308, 311, 312 placebo, 137 placebo effect, 137 Planck, Max, 24 Playskool, 111 Podesta, John, 97 point of no return, 244 Polaris, 67–68 polarity, 125–26 police, in organizations and projects, 253–54 politics, 70, 104 ads and statements in, 225–26 elections, 206, 218, 233, 241, 271, 293, 299 failure and, 47 influence in, 216 predictions in, 206 polls and surveys, 142–43, 152–54, 160 approval ratings, 152–54, 158 employee engagement, 140, 142 postmortems, 32, 92 Potemkin village, 228–29 potential energy, 112 power, 162 power drills, 296 power law distribution, 80–81 power vacuum, 259–60 practice, deliberate, 260–62, 264, 266 precautionary principle, 59–60 Predictably Irrational (Ariely), 14, 222–23 predictions and forecasts, 132, 173 market for, 205–7 superforecasters and, 206–7 PredictIt, 206 premature optimization, 7 premises, see principles pre-mortems, 92 present bias, 85, 87, 93, 113 preserving optionality, 58–59 pressure point, 112 prices, 188, 231, 299 arbitrage and, 282–83 bait and switch and, 228, 229 inflation in, 179–80, 182–83 loss leader strategy and, 236–37 manufacturer’s suggested retail, 15 monopolies and, 283 principal, 44–45 principal-agent problem, 44–45 principles (premises), 207 first, 4–7, 31, 207 prior, 159 prioritizing, 68 prisoners, 63, 232 prisoner’s dilemma, 212–14, 226, 234–35, 244 privacy, 55 probability, 132, 173, 194 bias, optimistic, 33 conditional, 156 probability distributions, 150, 151 bell curve (normal), 150–52, 153, 163–66, 191 Bernoulli, 152 central limit theorem and, 152–53, 163 fat-tailed, 191 power law, 80–81 sample, 152–53 pro-con lists, 175–78, 185, 189 procrastination, 83–85, 87, 89 product development, 294 product/market fit, 292–96, 302 promotions, 256, 275 proximate cause, 31, 117 proxy endpoint, 137 proxy metric, 139 psychology, 168 Psychology of Science, The (Maslow), 177 Ptolemy, Claudius, 8 publication bias, 170, 173 public goods, 39 punching above your weight, 242 p-values, 164, 165, 167–69, 172 Pygmalion effect, 267–68 Pyrrhus, King, 239 Qualcomm, 231 quantum physics, 200–201 quarantine, 234 questions: now what, 291 what if, 122, 201 why, 32, 33 why now, 291 quick and dirty, 234 quid pro quo, 215 Rabois, Keith, 72, 265 Rachleff, Andy, 285–86, 292–93 radical candor, 263–64 Radical Candor (Scott), 263 radiology, 291 randomized controlled experiment, 136 randomness, 201 rats, 51 Rawls, John, 21 Regan, Ronald, 183 real estate agents, 44–45 recessions, 121–22 reciprocity, 215–16, 220, 222, 229, 289 recommendations, 217 red line, 238 referrals, 217 reframe the problem, 96–97 refugee asylum cases, 144 regression to the mean, 146, 286 regret, 87 regulations, 183–84, 231–32 regulatory capture, 305–7 reinventing the wheel, 92 relationships, 53, 55, 63, 91, 111, 124, 159, 271, 296, 298 being locked into, 305 dating, 8–10, 95 replication crisis, 168–72 Republican Party, 104 reputation, 215 research: meta-analysis of, 172–73 publication bias and, 170, 173 systematic reviews of, 172, 173 see also experiments resonance, 293–94 response bias, 142, 143 responsibility, diffusion of, 259 restaurants, 297 menus at, 14, 62 RetailMeNot, 281 retaliation, 238 returns: diminishing, 81–83 negative, 82–83, 93 reversible decisions, 61–62 revolving door, 306 rewards, 275 Riccio, Jim, 306 rise to the occasion, 268 risk, 43, 46, 90, 288 cost-benefit analysis and, 180 de-risking, 6–7, 10, 294 moral hazard and, 43–45, 47 Road Ahead, The (Gates), 69 Roberts, Jason, 122 Roberts, John, 27 Rogers, Everett, 116 Rogers, William, 31 Rogers Commission Report, 31–33 roles, 256–58, 260, 271, 293 roly-poly toy, 111–12 root cause, 31–33, 234 roulette, 144 Rubicon River, 244 ruinous empathy, 264 Rumsfeld, Donald, 196–97, 247 Rumsfeld’s Rule, 247 Russia, 218, 241 Germany and, 70, 238–39 see also Soviet Union Sacred Heart University (SHU), 217, 218 sacrifice play, 239 Sagan, Carl, 220 sales, 81, 216–17 Salesforce, 299 same-sex marriage, 117, 118 Sample, Steven, 28 sample distribution, 152–53 sample size, 143, 160, 162, 163, 165–68, 172 Sánchez, Ricardo, 234 sanctions and fines, 232 Sanders, Bernie, 70, 182, 293 Sayre, Wallace, 74 Sayre’s law, 74 scarcity, 219, 220 scatter plot, 126 scenario analysis (scenario planning), 198–99, 201–3, 207 schools, see education and schools Schrödinger, Erwin, 200 Schrödinger’s cat, 200 Schultz, Howard, 296 Schwartz, Barry, 62–63 science, 133, 220 cargo cult, 315–16 Scientific Autobiography and other Papers (Planck), 24 scientific evidence, 139 scientific experiments, see experiments scientific method, 101–2, 294 scorched-earth tactics, 243 Scott, Kim, 263 S curves, 117, 120 secondary markets, 281–82 second law of thermodynamics, 124 secrets, 288–90, 292 Securities and Exchange Commission, U.S., 228 security, false sense of, 44 security services, 229 selection, adverse, 46–47 selection bias, 139–40, 143, 170 self-control, 87 self-fulfilling prophecies, 267 self-serving bias, 21, 272 Seligman, Martin, 22 Semmelweis, Ignaz, 25–26 Semmelweis reflex, 26 Seneca, Marcus, 60 sensitivity analysis, 181–82, 185, 188 dynamic, 195 Sequoia Capital, 291 Sessions, Roger, 8 sexual predators, 113 Shakespeare, William, 105 Sheets Energy Strips, 36 Shermer, Michael, 133 Shirky, Clay, 104 Shirky principle, 104, 112 Short History of Nearly Everything, A (Bryson), 50 short-termism, 55–56, 58, 60, 68, 85 side effects, 137 signal and noise, 311 significance, 167 statistical, 164–67, 170 Silicon Valley, 288, 289 simulations, 193–95 simultaneous invention, 291–92 Singapore math, 23–24 Sir David Attenborough, RSS, 35 Skeptics Society, 133 sleep meditation app, 162–68 slippery slope argument, 235 slow (high-concentration) thinking, 30, 33, 70–71 small numbers, law of, 143, 144 smartphones, 117, 290, 309, 310 smoking, 41, 42, 133–34, 139, 173 Snap, 299 Snowden, Edward, 52, 53 social engineering, 97 social equality, 117 social media, 81, 94, 113, 217–19, 241 Facebook, 18, 36, 94, 119, 219, 233, 247, 305, 308 Instagram, 220, 247, 291, 310 YouTube, 220, 291 social networks, 117 Dunbar’s number and, 278 social norms versus market norms, 222–24 social proof, 217–20, 229 societal change, 100–101 software, 56, 57 simulations, 192–94 solitaire, 195 solution space, 97 Somalia, 243 sophomore slump, 145–46 South Korea, 229, 231, 238 Soviet Union: Germany and, 70, 238–39 Gosplan in, 49 in Cold War, 209, 235 space exploration, 209 spacing effect, 262 Spain, 243–44 spam, 37, 161, 192–93, 234 specialists, 252–53 species, 120 spending, 38, 74–75 federal, 75–76 spillover effects, 41, 43 sports, 82–83 baseball, 83, 145–46, 289 football, 226, 243 Olympics, 209, 246–48, 285 Spotify, 299 spreadsheets, 179, 180, 182, 299 Srinivasan, Balaji, 301 standard deviation, 149, 150–51, 154 standard error, 154 standards, 93 Stanford Law School, x Starbucks, 296 startup business idea, 6–7 statistics, 130–32, 146, 173, 289, 297 base rate in, 157, 159, 160 base rate fallacy in, 157, 158, 170 Bayesian, 157–60 confidence intervals in, 154–56, 159 confidence level in, 154, 155, 161 frequentist, 158–60 p-hacking in, 169, 172 p-values in, 164, 165, 167–69, 172 standard deviation in, 149, 150–51, 154 standard error in, 154 statistical significance, 164–67, 170 summary, 146, 147 see also data; experiments; probability distributions Staubach, Roger, 243 Sternberg, Robert, 290 stock and flow diagrams, 192 Stone, Douglas, 19 stop the bleeding, 234 strategy, 107–8 exit, 242–43 loss leader, 236–37 pivoting and, 295–96, 298–301, 308, 311, 312 tactics versus, 256–57 strategy tax, 103–4, 112 Stiglitz, Joseph, 306 straw man, 225–26 Streisand, Barbra, 51 Streisand effect, 51, 52 Stroll, Cliff, 290 Structure of Scientific Revolutions, The (Kuhn), 24 subjective versus objective, in organizational culture, 274 suicide, 218 summary statistics, 146, 147 sunk-cost fallacy, 91 superforecasters, 206–7 Superforecasting (Tetlock), 206–7 super models, viii–xii super thinking, viii–ix, 3, 316, 318 surface area, 122 luck, 122, 124, 128 surgery, 136–37 Surowiecki, James, 203–5 surrogate endpoint, 137 surveys, see polls and surveys survivorship bias, 140–43, 170, 272 sustainable competitive advantage, 283, 285 switching costs, 305 systematic review, 172, 173 systems thinking, 192, 195, 198 tactics, 256–57 Tajfel, Henri, 127 take a step back, 298 Taleb, Nassim Nicholas, 2, 105 talk past each other, 225 Target, 236, 252 target, measurable, 49–50 taxes, 39, 40, 56, 104, 193–94 T cells, 194 teams, 246–48, 275 roles in, 256–58, 260 size of, 278 10x, 248, 249, 255, 260, 273, 280, 294 Tech, 83 technical debt, 56, 57 technologies, 289–90, 295 adoption curves of, 115 adoption life cycles of, 116–17, 129, 289, 290, 311–12 disruptive, 308, 310–11 telephone, 118–19 temperature: body, 146–50 thermostats and, 194 tennis, 2 10,000-Hour Rule, 261 10x individuals, 247–48 10x teams, 248, 249, 255, 260, 273, 280, 294 terrorism, 52, 234 Tesla, Inc., 300–301 testing culture, 50 Tetlock, Philip E., 206–7 Texas sharpshooter fallacy, 136 textbooks, 262 Thaler, Richard, 87 Theranos, 228 thermodynamics, 124 thermostats, 194 Thiel, Peter, 72, 288, 289 thinking: black-and-white, 126–28, 168, 272 convergent, 203 counterfactual, 201, 272, 309–10 critical, 201 divergent, 203 fast (low-concentration), 30, 70–71 gray, 28 inverse, 1–2, 291 lateral, 201 outside the box, 201 slow (high-concentration), 30, 33, 70–71 super, viii–ix, 3, 316, 318 systems, 192, 195, 198 writing and, 316 Thinking, Fast and Slow (Kahneman), 30 third story, 19, 92 thought experiment, 199–201 throwing good money after bad, 91 throwing more money at the problem, 94 tight versus loose, in organizational culture, 274 timeboxing, 75 time: management of, 38 as money, 77 work and, 89 tipping point, 115, 117, 119, 120 tit-for-tat, 214–15 Tōgō Heihachirō, 241 tolerance, 117 tools, 95 too much of a good thing, 60 top idea in your mind, 71, 72 toxic culture, 275 Toys “R” Us, 281 trade-offs, 77–78 traditions, 275 tragedy of the commons, 37–40, 43, 47, 49 transparency, 307 tribalism, 28 Trojan horse, 228 Truman Show, The, 229 Trump, Donald, 15, 206, 293 Trump: The Art of the Deal (Trump and Schwartz), 15 trust, 20, 124, 215, 217 trying too hard, 82 Tsushima, Battle of, 241 Tupperware, 217 TurboTax, 104 Turner, John, 127 turn lemons into lemonade, 121 Tversky, Amos, 9, 90 Twain, Mark, 106 Twitter, 233, 234, 296 two-front wars, 70 type I error, 161 type II error, 161 tyranny of small decisions, 38, 55 Tyson, Mike, 7 Uber, 231, 275, 288, 290 Ulam, Stanislaw, 195 ultimatum game, 224, 244 uncertainty, 2, 132, 173, 180, 182, 185 unforced error, 2, 10, 33 unicorn candidate, 257–58 unintended consequences, 35–36, 53–55, 57, 64–65, 192, 232 Union of Concerned Scientists (UCS), 306 unique value proposition, 211 University of Chicago, 144 unknown knowns, 198, 203 unknowns: known, 197–98 unknown, 196–98, 203 urgency, false, 74 used car market, 46–47 U.S.
Against Empathy: The Case for Rational Compassion by Paul Bloom
affirmative action, Albert Einstein, Asperger Syndrome, Atul Gawande, Columbine, David Brooks, Donald Trump, effective altruism, Ferguson, Missouri, impulse control, meta analysis, meta-analysis, Paul Erdős, period drama, Peter Singer: altruism, publication bias, Ralph Waldo Emerson, replication crisis, Ronald Reagan, social intelligence, Stanford marshmallow experiment, Steven Pinker, theory of mind, Walter Mischel, Yogi Berra
It turns out, then, that all the empathy measures that are commonly used are actually measures of a cluster of things—including empathy, but also concern and compassion, as well as some traits, such as being cool-headed in an emergency, that might have little to do with empathy in any sense of the term. Finally, when it comes to looking at research concerning the relationship between empathy and good behavior, there is the issue of publication bias. Researchers who study the effects of empathy are typically hoping and expecting that empathy does have effects—nobody does an experiment hoping to find nothing. Studies that fail to find an effect are therefore less likely to be submitted for publication (the so-called file drawer problem), and if such work is submitted, it’s more difficult to get published, because null effects are notoriously uninteresting to reviewers and editors.
(documentary), 50 food aid, 99 football, and violence, 187 foreign aid, 99 forgiveness, 25 Fourth Amendment, 37 Freddie Kruger (character), 180 free speech, 123–26 free trade, 112, 117 free will, 218–19, 221 Freud, Sigmund, 5, 145, 216 friendship, 149–54, 158–59 Fritz, Heidi, 133–35 Gandhi, Mahatma, 159–60 Garner, Eric, 118 Gawande, Atul, 145 gay marriage, 53, 55, 116, 122 Gaza War, 186, 188–89, 190 Gazzaniga, Michael, 220 gender differences, 81, 129, 133–36 objectification, 203–4, 206 genes, 8, 94–95, 154, 169, 195 Ghiselin, Michael, 166 Gladwell, Malcolm, 231–32 Glover, Jonathan, 74, 188 Godwin, Morgan, 202 Godwin’s Law, 63 Goebbels, Joseph, 196 Goodman, Charles, 138 goodness (good actions/behaviors), 41–42, 85–86, 101–6 effective altruism, 102–6, 238–39 empathy-altruism hypothesis, 25, 85–86, 168 high intelligence and, 233 measuring empathy and, 41–42, 77–82 publication bias and measuring empathy, 82–83 Gore, Al, 49–50, 121 Göring, Hermann, 196 Gourevitch, Philip, 93 greed, 188 Greene, Joshua, 10 guilt, 44, 87, 182, 198 gun control, 115, 116, 119, 122–23 gut feelings, 7, 213–14 Habitat for Humanity, 88 Haidt, Jonathan, 6, 120, 223 Haldane, J. B. S., 169 Hamas, 189–90 Hannibal Lecter (character), 180–81 Hare, Robert, 197, 198, 199 Harris, Lasana, 69 Harris, Paul, 174, 175 Harris, Sam, 10, 218 Harris, Thomas, 180–81 Helgeson, Vicki, 133–35 helping others.
., 178 Paul, Laurie, 147–48 Paul, Ron, 118 Personal Concern scale, 80–81 personal distress, 25 Personal Distress scale, 79–81 Perspective Taking scale, 78–81 physicalism, 148 physician-patient relationship, 143–45, 146–47 Pinker, Steven, 10, 18–19, 74–75, 239–40 moralization gap and, 181, 184 self-control and, 234 threshold effect and, 231 Pitkin, Aaron, 46 pity, 40, 100 Plato, 214 poker, 28 Poland, Hitler’s invasion of, 193 police shootings, 4, 19–20, 205 political orientation and language, 114–18 politics, 113–27 free speech and, 123–26 legal context, 125–26 liberal policies and empathy, 113–14, 118–25 rationality and irrationality in, 235–37 pornography, depiction of women in, 203–4 Poulin, Michael, 193–95 prefrontal cortex, 61, 71 presidential election of 2012, 117–18, 119 Prinz, Jesse, 10, 22, 200, 210–11 prison rape, 93 progressives (progressivism), 113–14, 118–27 political orientation and language, 114–18 projective empathy, 70–71, 155 “prosocial concern,” 62 psychoanalysis, 5, 144, 145, 216 psychological egoism, 72–74, 75–76 psychopaths (psychopathy), 42, 197–201 lack of self-control and malicious nature of, 42, 199–201 myth of pure evil, 181, 184 neuroscience of, 47, 71–73 Psychopathy Checklist, 197–201, 198 publication bias, 82–83 punishment, 161, 185, 186, 192, 195–96, 207, 209, 225 purity, 117–18, 224 qualia, and knowledge argument, 148 Rachels, James, 52 racial bias, 226 racism, 9, 48–49, 202–3 Rai, Tage, 184–85, 186 Raine, Adrian, 179 Rand, David, 7 rape, 23, 34, 35, 93, 182, 192, 206 rationality. See reason Reagan, Ronald, 90, 121 reason, 213–41 as basis for morality, 5–6, 8–9, 10, 16, 39, 44, 51–54 definition of, 51 neuroscience and attack on, 216–21 in political domains, 235–38 positive case for, 230–35 relationship between IQ and success, 231–33 self-control and, 234–35 social psychology and attack on, 221–29 religious belief, 25, 27 replication, in social psychology, 223–24 retaliation, 182–83 Ricard, Matthieu, 10, 137–39 Rifkin, Jeremy, 20 righteous rage, 210–11 Rizzolatti, Giacomo, 62–63 Roberts, John, 125 Romney, Mitt, 119 Rousseau, Jean-Jacques, 73–74 Rubenstein, Jennifer, 102–3 Russell, Bertrand, 109 Rust, Joshua, 233 sadists, 183–84, 196 sanctity, and conservatives, 120 Sandy Hook Elementary School shooting, 1–2, 31–33, 90 Santorum, Rick, 117–18 Satan, 180 Save the Children, 74–75 Scarry, Elaine, 10, 106–9 Schelling, Thomas, 88–89 Schiller, Robert, 152 Schindler’s List (movie), 92–93 school shootings, 1–2, 31–33, 95 Schwitzgebel, Eric, 233 Scott, Miles, 96–97 Scottish Enlightenment, 7, 16–17, 165–66 self and other, neuroscience of, 62–68 self-awareness, 52, 68, 236 self-control, 42, 179, 234–35 self-defense, 186–87 self-interest, 52, 167–69 disaster theory and, 93–94 free speech and, 124–25 incentives and, 57–58 selfish-motivation theory, 72–74, 75–76 separate processes theory, 71–72 September 11 attacks, 2, 90, 143, 186, 235 sex differences, 81, 129, 133–36 objectification, 203–4, 206 sexism, 206 sexual assault, 181, 182, 192 sexual harassment, 157, 206 shallow affect, 198, 200 shame, 44, 87, 156–57 Sheri Summers (character), 25, 86–87 Shermer, Michael, 10 Sidgwick, Henry, 29 Silence of the Lambs (movie), 180–81 Singer, Peter, 10, 29 charitable giving, 45, 96–97, 98–99 effective altruism, 103, 104–6, 160–61, 238, 239 Singer, Tania, 10, 43, 137–38, 139 Skeem, Jennifer, 197, 200 slavery, 112, 202 sleeping pills, 219 Slote, Michael, 155 Slovic, Paul, 90–91 Smith, Adam, 44, 165–66, 235, 240 China example, 91–92 empathic experience, 68, 69 friendship and empathy, 130, 150–55 “sympathy,” 16–17, 35, 39, 165 violence and empathy, 191–92 Smith, David Livingstone, 181, 202, 204–5, 206 Smith, Rebecca, 34 social cognition, 17, 62 social intelligence, 17 “social neuroscience,” 60 social psychology of reason, 221–29 sociopaths, 181, 197.
Overdosed America: The Broken Promise of American Medicine by John Abramson
germ theory of disease, Louis Pasteur, medical malpractice, medical residency, meta analysis, meta-analysis, p-value, placebo effect, profit maximization, profit motive, publication bias, RAND corporation, randomized controlled trial, selective serotonin reuptake inhibitor (SSRI), stem cell, Thomas Kuhn: the structure of scientific revolutions
The article also reported that 92 percent of these ads were in some violation of FDA rules. Writing in The Lancet in 2003, Dr. Fletcher said that as punishment for publishing this article, the pharmaceutical industry “withdrew many adverts” and showed that it was “willing to flex its considerable muscles when it felt its interests were threatened.” This is a price that medical journal editors would prefer not to pay. NOT TELLING THE WHOLE TRUTH: PUBLICATION BIAS Even if a doctor could keep up with all the studies that were published, he or she would still have a limited and skewed view of the real evidence. Notwithstanding all the potential ways that research can be tipped in favor of a sponsor’s product, clinical trials still tend to reveal the truth about whether a new therapy is effective—or not. The problem is that research that shows that a product is not effective or safe can be hidden away, that is, the “knowledge” can be filtered to let through findings that favor the sponsor’s product, making it difficult for even the most fastidious doctors to discover the truth.
In another study, researchers in the United States obtained data under the Freedom of Information Act from all of the studies (both published and unpublished) that the FDA had reviewed in the process of approving seven new antidepressants (Prozac, Zoloft, Paxil, Effexor, Serzone, Remeron, and Wellbutrin SR) between 1987 and 1997—a total of 5200 pages of documents. The results of all of the “pivotal” studies (those deemed to be of high enough quality to be used in the FDA’s determinations) for these seven antidepressants were then put together to assess the overall effect of the new drugs. By looking at all the studies, the researchers avoided the distortion of “publication bias” and were able to determine whether or not the scientific evidence really showed that the new antidepressants are more effective and safer than the older ones. When all the evidence is considered, it turns out that the new antidepressant drugs are no more effective than the older tricyclic antidepressants (the classic being amitriptyline, brand name Elavil). More important, the new antidepressants were found to be not even 10 percent more effective than the placebos: Symptoms of depression improved by 30.9 percent in the people who took the placebos; by 40.7 percent in the people who took the newer antidepressants; and by 41.7 percent in the people who took the older antidepressants.
See also medical research absolute vs. relative risk and, 14–16, 165, 166, 229 advertising and research companies and, 109–10 Celebrex and Vioxx research (see Celebrex and Vioxx) cholesterol research (see cholesterol guidelines of 2001) commercial funding, 94–97 (see also drug companies; funding) commercial goals vs. health goals, 21–22, 50–51, 53, 241–44 conflicts of interest and (see conflicts of interest) damage control and, 107–9 data manipulation, 34–36 data omission, 29–31 data transparency and, 27–28, 94, 105–6, 251–52 dosage manipulation, 101–2 failure to compare existing therapies, 17, 102–3 FDA drug approval and Rezulin, 86–88 ghostwriters and, 106–7 hormone replacement therapy (see hormone replacement therapy) implantable defibrillators, 98–101 independent review for, 249–53 medical journals and, 25–27, 37–38, 93–94, 96–97 (see also medical journals) osteoporosis research, 211–20 Paxil research, 243 premature termination of research, 104–5 publication bias as, 113–17 research design changes as, 31 septic shock research, 161–63 stroke research, 13–22 unbiased information vs., 167 unrepresentative patients, 16–17, 33, 103–4, 206–8, 251 commercial speech, 37–38, 157–59 conflicts of interest academic experts, xxii, 18, 243 cholesterol guidelines, 135, 147–48 clinical guideline experts, xxi, 127–28, 133–35, 146–48, 227, 249–50 continuing medical education, 121–23 damage control, 109 FDA, 85–87, 89–90 ghostwriters, 106–7 hormone replacement therapy, 60–61 medical journal, 26 medical news stories, 166–67 NIH researchers, 86–90 independent review and, 258–59 surgeons, 177–78 confounding factors, 66–67 consciousness, 206–8 consulting contracts, 88–90, 109, 249.
Trick or Treatment: The Undeniable Facts About Alternative Medicine by Edzard Ernst, Simon Singh
animal electricity, Barry Marshall: ulcers, Berlin Wall, correlation does not imply causation, false memory syndrome, Florence Nightingale: pie chart, germ theory of disease, John Snow's cholera map, Louis Pasteur, meta analysis, meta-analysis, placebo effect, profit motive, publication bias, randomized controlled trial, Ronald Reagan, Simon Singh, The Design of Experiments, the scientific method
Therefore, either Eastern researchers or Western researchers must be wrong – as it happens, there are good reasons to believe that the problem lies in the East. The crude reason for blaming Chinese researchers for the discrepancy is that their results are simply too good to be true. This criticism has been confirmed by careful statistical analyses of all the Chinese results, which demonstrate beyond all reasonable doubt that Chinese researchers are guilty of so-called publication bias. Before explaining the meaning of publication bias, it is important to stress that this is not necessarily a form of deliberate fraud, because it is easy to conceive of situations when it can occur due to an unconscious pressure to get a particular result. Imagine a Chinese researcher who conducts an acupuncture trial and achieves a positive result. Acupuncture is a major source of prestige for China, so the researcher quickly and proudly publishes his positive result in a journal.
The key point is that this second piece of research might never be published for a whole range of possible reasons: maybe the researcher does not see it as a priority, or he thinks that nobody will be interested in reading about a negative result, or he persuades himself that this second trial must have been badly conducted, or he feels that this latest result would offend his peers. Whatever the reason, the researcher ends up having published the positive results of the first trial, while leaving the negative results of the second trial buried in a drawer. This is publication bias. When this sort of phenomenon is multiplied across China, then we have dozens of published positive trials, and dozens of unpublished negative trials. Therefore, when the WHO conducted a review of the published literature that relied heavily on Chinese research its conclusion was bound to be skewed – such a review could never take into account the unpublished negative trials. The WHO report was not just biased and misleading; it was also dangerous because it was endorsing acupuncture for a whole range of conditions, some of which were serious, such as coronary heart disease.
The End of Big: How the Internet Makes David the New Goliath by Nicco Mele
4chan, A Declaration of the Independence of Cyberspace, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apple's 1984 Super Bowl advert, barriers to entry, Berlin Wall, big-box store, bitcoin, business climate, call centre, Cass Sunstein, centralized clearinghouse, Chelsea Manning, citizen journalism, cloud computing, collaborative consumption, collaborative editing, commoditize, creative destruction, crony capitalism, cross-subsidies, crowdsourcing, David Brooks, death of newspapers, disruptive innovation, Donald Trump, Douglas Engelbart, Douglas Engelbart, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, Filter Bubble, Firefox, global supply chain, Google Chrome, Gordon Gekko, Hacker Ethic, Jaron Lanier, Jeff Bezos, jimmy wales, John Markoff, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, Lean Startup, Mark Zuckerberg, minimum viable product, Mitch Kapor, Mohammed Bouazizi, Mother of all demos, Narrative Science, new economy, Occupy movement, old-boy network, peer-to-peer, period drama, Peter Thiel, pirate software, publication bias, Robert Metcalfe, Ronald Reagan, Ronald Reagan: Tear down this wall, sharing economy, Silicon Valley, Skype, social web, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, Ted Nelson, Telecommunications Act of 1996, telemarketer, The Wisdom of Crowds, transaction costs, uranium enrichment, Whole Earth Catalog, WikiLeaks, Zipcar
Nielsen and other advocates for “open science” say science can accomplish much more, much faster, in an environment of friction-free collaboration over the Internet.25 Peer review may provide accountability, but it is in many ways deeply flawed and inadequate in the digital age. Peer-reviewed publication takes on average about two years, and many scientific journals costs thousands of dollars a year for subscriptions. Not only that, but if scientific research fails, it usually does not get written up and published. Who wants to publish an article that says, “we tried this and it didn’t work”? “Publication bias” is a well-known challenge in academia. A major review of more than 4,600 peer-reviewed academic papers across a range of disciplines and a range of countries found that over the last twenty years, positive results increased by almost 25%.26 And yet failure is a crucial part of the scientific process. To better figure out what works, you need to know what doesn’t work. Despite the entrenched function of peer review within the academic establishment, online correctives and alternatives have proliferated.
Harry Lewis, Excellence Without a Soul: How a Great University Forgot Education (New York: PublicAffairs, 2006), 8. 5. http://www.usnews.com/opinion/articles/2011/03/18/a-harvard-education-isnt-as-advertised 6. http://www.demos.org/publication/great-cost-shift-how-higher-education-cuts-undermine-future-middle-class 7. http://www.washingtonpost.com/opinions/when-it-comes-to-e-mailed-political-rumors-conservatives-beat-liberals/2011/11/17/gIQAyycZWN_story.html 8. http://www.csmonitor.com/The-Culture/Family/2012/0617/Bachelor-s-degree-Has-it-lost-its-edge-and-its-value 9. http://chronicle.com/blogs/innovations/why-did-17-million-students-go-to-college/27634 10. http://pewresearch.org/pubs/1993/survey-is-college-degree-worth-cost-debt-college-presidents-higher-education-system 11. http://pewresearch.org/pubs/1993/survey-is-college-degree-worth-cost-debt-college-presidents-higher-education-system 12. http://www.businessweek.com/technology/content/may2011/tc20110524_317819.htm 13. http://techcrunch.com/2011/04/10/peter-thiel-were-in-a-bubble-and-its-not-the-internet-its-higher-education/ 14. http://ocw.mit.edu/about/newsletter/archive/2011-10/ 15. http://techcrunch.com/2011/10/19/khan-academy-triples-unique-users-to-3-5-million/ 16. http://blogs.reuters.com/felix-salmon/2012/01/31/udacitys-model/ 17. http://www.britannica.com/blogs/2008/04/the-great-unbundling-newspapers-the-net/ 18. http://www.theatlantic.com/technology/archive/2012/01/the-great-unbundling-of-the-university/251831/ 19. http://www.centerforcollegeaffordability.org/uploads/ForProfit_HigherEd.pdf 20. http://www.bloomberg.com/news/2011-10-19/apollo-fourth-quarter-profit-sales-top-analysts-estimates-1-.html 21. http://nber.org/papers/w18201 22. http://www.theatlantic.com/business/archive/2012/07/why-the-internet-isnt-going-to-end-college-as-we-know-it/259378/ 23. http://toolserver.org/~daniel/WikiSense/Contributors.php?wikilang=en&wikifam=.wikipedia.org&grouped=on&page=Abraham_Lincoln 24. http://storify.com/jcstearns/50-years-after-the-vast-wast 25. http://www.nytimes.com/2012/01/17/science/open-science-challenges-journal-tradition-with-web-collaboration.html?pagewanted=all 26. http://www.theatlantic.com/health/archive/2011/10/publication-bias-may-permanently-damage-medical-research/246616/ 27. http://usefulchem.wikispaces.com/ 28. David Weinberger, Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room (New York: Basic Books, 2011), 139. 29. Ibid., 140. 30. http://blogs.discovermagazine.com/badastronomy/2007/07/11/discover-new-galaxies/ 31. http://www.hbs.edu/research/pdf/07-050.pdf 32. http://www.parade.com/hot-topics/2008/09/secrets-of-great-presidents_233. http://lisaneal.files.wordpress.com/2009/02/alt12-gualtieri1.pdf 34. http://www.thedailybeast.com/newsweek/2012/04/15/why-your-doctor-has-no-time-to-see-you.html 35. http://papers.ssrn.com/sol3/papers.cfm?
Humble Pi: A Comedy of Maths Errors by Matt Parker
8-hour work day, Affordable Care Act / Obamacare, bitcoin, British Empire, Brownian motion, Chuck Templeton: OpenTable:, collateralized debt obligation, computer age, correlation does not imply causation, crowdsourcing, Donald Trump, Flash crash, forensic accounting, game design, High speed trading, Julian Assange, millennium bug, Minecraft, obamacare, orbital mechanics / astrodynamics, publication bias, Richard Feynman, Richard Feynman: Challenger O-ring, selection bias, Tacoma Narrows Bridge, Therac-25, value at risk, WikiLeaks, Y2K
When a company runs a drug trial on some new medication or medical intervention they have been working on, they want to show that it performs better than either no intervention or other current options. At the end of a long and expensive trial, if the results show that a drug has no benefit (or a negative one), there is very little motivation for the company to publish that data. It’s a kind of ‘publication bias’. An estimated half of all drug-trial results never get published. A negative result from a drug trial is twice as likely to remain unpublished as a positive result. Withholding any drug-trial data can put people’s lives at risk, possibly more so than any other mistake I’ve mentioned in this book. Engineering and aviation disasters can result in hundreds of deaths. Drugs can have far wider impacts.
The air force tried to get an academic anthropological department from a university involved, but no one was interested. 2 The extra sets of data were made by slowly evolving the data via tiny changes which moved the data points towards a new picture but didn’t change the averages and standard deviations. The software to do this has been made freely available. 3 Their study was finally published thirteen years later, in 1993, as an example of publication bias. 4 In the interest of full disclosure, this is before I was writing for the Guardian myself, but the article was written by my friend Ben Goldacre, of AllTrials fame. Twelve: Tltloay Rodanm 1 At the time of writing, ERNIE is no longer on public display at the Science Museum. 2 It pleases me greatly that part of the required word count of my book has now officially been randomly generated. 3 This was still in the era when the US government controlled the export of software with strong encryption, as they considered such cryptography as munitions.
Testosterone Rex: Myths of Sex, Science, and Society by Cordelia Fine
assortative mating, Cass Sunstein, credit crunch, Donald Trump, Downton Abbey, Drosophila, epigenetics, experimental economics, gender pay gap, George Akerlof, glass ceiling, helicopter parent, longitudinal study, meta analysis, meta-analysis, phenotype, publication bias, risk tolerance
The results from very large studies, being more “precise,” should tend to cluster close to the “true” size of the effect. Smaller studies by contrast, being subject to more random error because of their small, idiosyncratic samples, will be scattered over a wider range of effect sizes. Some small studies will greatly overestimate a difference; others will greatly underestimate it (or even “flip” it in the wrong direction). The next part is simple but brilliant. If there isn’t publication bias toward reports of greater male risk taking, these over- and underestimates of the sex difference should be symmetrical around the “true” value indicated by the very large studies. This, with quite a bit of imagination, will make the plot of the data look like an upside-down funnel. (Personally, my vote would have been to call it the candlestick plot, but I wasn’t consulted.) But if there is bias, then there will be an empty area in the plot where the smaller samples that underestimated the difference, found no differences, or yielded greater female risk taking should be.
Herbert (2015), ibid. Quoted on p. 52. 55. Hönekopp, J., & Watson, S. (2011). Meta-analysis of the relationship between digit-ratio 2D:4D and aggression. Personality and Individual Differences, 51(4), 381–386. A small correlation was found for men only (r = –.08 for the left hand and r = –.07 for the right hand), but this reduced to a nonsignificant correlation for r = –.03 after correction for weak publication bias. 56. Voracek et al. (2010), ibid. The authors note the complexity of the biological system thought to underlie sensation seeking, as well as the many psychosocial factors known to influence it, and thus conclude that “Given these knowns, it appears unsurprising that rather simplistic approaches, such as studies only utilizing 2D:4D (a putative, not yet sufficiently validated marker of prenatal testosterone), are prone to be barren of results.”
Wall Street: How It Works And for Whom by Doug Henwood
accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, affirmative action, Andrei Shleifer, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, borderless world, Bretton Woods, British Empire, business cycle, capital asset pricing model, capital controls, central bank independence, computerized trading, corporate governance, corporate raider, correlation coefficient, correlation does not imply causation, credit crunch, currency manipulation / currency intervention, David Ricardo: comparative advantage, debt deflation, declining real wages, deindustrialization, dematerialisation, diversification, diversified portfolio, Donald Trump, equity premium, Eugene Fama: efficient market hypothesis, experimental subject, facts on the ground, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, full employment, George Akerlof, George Gilder, hiring and firing, Hyman Minsky, implied volatility, index arbitrage, index fund, information asymmetry, interest rate swap, Internet Archive, invisible hand, Irwin Jacobs, Isaac Newton, joint-stock company, Joseph Schumpeter, kremlinology, labor-force participation, late capitalism, law of one price, liberal capitalism, liquidationism / Banker’s doctrine / the Treasury view, London Interbank Offered Rate, Louis Bachelier, market bubble, Mexican peso crisis / tequila crisis, microcredit, minimum wage unemployment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, oil shock, Paul Samuelson, payday loans, pension reform, plutocrats, Plutocrats, price mechanism, price stability, prisoner's dilemma, profit maximization, publication bias, Ralph Nader, random walk, reserve currency, Richard Thaler, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, selection bias, shareholder value, short selling, Slavoj Žižek, South Sea Bubble, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Market for Lemons, The Nature of the Firm, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, transcontinental railway, women in the workforce, yield curve, zero-coupon bond
But in surveys of employers taken just before and after changes in the minimum wage, David Card and Alan Krueger (1995) showed that this just isn't true. They paused for a few pages in the middle of their book. Myth and Measurement, to review some reasons why the academic literature has almost unanimously found the minimum wage guilty as charged. They surmised that earlier studies showing that higher wages reduced employment were the result of "publication bias" among journal editors. They also surmised, very diplomatically, that economists have been aware of this bias, and played those notorious scholarly games, "specification searching and data mining" — bending the numbers to obtain the desired result. They also noted that some of the early studies were based on seriously flawed data, but since the results were desirable from both the political and professional points of view, they went undiscovered for several years.
See money managers portfolio vs. direct investment, 109 Post Keynesian Thought (PKT) computer network, 243 post-Keynesianism, 217-224 defined, 241-242 see also money, endogenous postmodernism. 237, 245 present value, 119-120 priest, banker's advice more useful than, 225 primitive accumulation, 252 prisoners' dilemma, 171, 183 Pritzker family, 271 private placements, 75 privatization, 110 of economic statistics, I36 returning capital flight and, 295 Social Security, 303-307 production, 241 socialization of, 240 productivity, 299 failure to boom in 1980s, 183 profit(s) maximization Galbraith on, 259 Herman on, 260 and modern corporation, 254 transformation into interest, 73-74, 238 Progressive Era, 94 property relations and social investing, 314- 315 prostitutes. Wail Streeters as customers, 79 protectionism, 295, 300 Proudhonism, 301 The Prudential, 262 investigations of, 304 psychoanalysis, 315 psychology and stock prices, 176-178; see also Keynes, John Maynard; money, psychology of public goods, 143 public relations, ll6 publication bias, 141 Pujo Committee, 260 Pulitzer Prize, 298 puritans of finance, 196 puts, 30; see also derivatives q ratio and capital expenditures, 145-148 and LBOs, 283 and M&A, 148, 284, 299 as stock market predictors, 148 Quan, Tracy, 79 race financial workers, 78 and wealth distribution, 69-70 racism, 98 among goldbugs, 48 Keynes's, 212 railroads and modern corporation, 188 Rainforest Crunch, 313 Rand, Ayn, 47, 89 random walk, 164 Rathenau, Walther, 256 rational expectations, l6l; see fl&o efficient market theory rationality, assumption of, 175 Ravenscraft, David, 279, 283-284 Reagan, Ronald, 87 real estate, 80 real sector predicting the financial, 125-126; see also business cycles Reconstruction Finance Corp., 286 reform, financial, difficulty of, 302 Regan, Edward, 27 regulation, government, overview, 90-99 Reich, Robert, 131 Relational Investors, 289 relationship investing, 293 religion banking and, 225 and belief in markets, 150 monetarism as, 242 and money, 225 restrictions on usury, 42 rentiers apologists, 293 appropriation of worker savings, 239 capture of Clinton administration, 134 consciousness, 237, 238; see also money, psychology of corporate cash flow share, 73-74 dominance of political discourse, 294 early 1990s riot, 288-291 euthanasia of, 210 evolutionary role, 8 formation through financial markets, 238 growing assertiveness, 207 proliferate over time, 215, 236 who needs them?
Peers, Pirates, and Persuasion: Rhetoric in the Peer-To-Peer Debates by John Logie
1960s counterculture, Berlin Wall, book scanning, cuban missile crisis, Fall of the Berlin Wall, Hacker Ethic, Isaac Newton, Marshall McLuhan, moral panic, mutually assured destruction, peer-to-peer, plutocrats, Plutocrats, pre–internet, publication bias, Richard Stallman, Search for Extraterrestrial Intelligence, search inside the book, SETI@home, Silicon Valley, slashdot, Steve Jobs, Steven Levy, Stewart Brand, Whole Earth Catalog
., copyrights and patents) are offered by the people, via Congress, and for the people, as an incentive for further production from authors and inventors. This represents a subtle but significant break from a broader European tradition in which the so-called “natural rights” of the author or inventor function as the bases for intellectual property protections. The 1991 Supreme Court’s ringing endorsement of copyright’s inherent public bias in the Feist case (once again: “The primary objective of copyright is not to reward the labor of authors, but ‘[t]o promote the Progress of Science and useful Arts.’”) almost certainly emboldened Robertson as he set about developing the my.mp3.com service. Robertson even agreed with the RIAA that Napster was enabling piracy. As the Napster case was still wending its way through the courts, Robertson was sharply critical of his fellow RIAA defendant.
Fun Inc. by Tom Chatfield
Alexey Pajitnov wrote Tetris, Any sufficiently advanced technology is indistinguishable from magic, Boris Johnson, cloud computing, cognitive dissonance, computer age, credit crunch, game design, invention of writing, longitudinal study, moral panic, publication bias, Silicon Valley, Skype, stem cell, upwardly mobile
Its author, Dr Christopher John Ferguson, an assistant professor of psychology at Texas A&M International University, set out to compare every article published in a peer-reviewed journal between 1995 and April 2007 that in some way investigated the effect of playing violent video games on some measure of aggressive behaviour. A total of seventeen published studies matched these criteria – and Ferguson’s conclusions were unexpectedly unequivocal. ‘Once corrected for publication bias,’ he reported, ‘studies of video game violence provided no support for the hypothesis that violent video game-playing is associated with higher aggression.’ Moreover, he added, the question ‘do violent games cause violence?’ is itself flawed in that ‘it assumes that such games have only negative effects and ignores the possibility of positive effects’ such as the possibility that violent games allow ‘catharsis’ of a kind in their players.
How Cycling Can Save the World by Peter Walker
active transport: walking or cycling, bike sharing scheme, Boris Johnson, car-free, correlation does not imply causation, Enrique Peñalosa, Intergovernmental Panel on Climate Change (IPCC), Kickstarter, meta analysis, meta-analysis, New Journalism, New Urbanism, post-work, publication bias, the built environment, traffic fines, transit-oriented development, urban planning
CHAPTER 7 1 Michael Polhamus, “Bill Would Require Neon Clothes, Government ID for Cyclists,” Jackson Hole News and Guide, January 30, 2015, http://www.jhnewsandguide.com/jackson_hole_daily/local/bill-would-require-neon-clothes-government-id-for-cyclists/article_d53b9712-2e93-517d-9e33-8f13d693ba21.html. 2 Wes Johnson, “Missouri Bill Requires Bicyclists to Fly 15-Foot Flag on Country Roads,” Springfield News-Leader, January 14, 2016. 3 “School Pupils Encouraged to Wear Hi-Vis Vests in Road Safety Scheme,” Grimsby Telegraph, January 23, 2012, http://www.grimsbytelegraph.co.uk/school-pupils-encouraged-wear-hi-vis-vests-road/story-15010565-detail/story.html. 4 Chris Boardman, “Why I Didn’t Wear a Helmet on BBC Breakfast,” BritishCycling.org, November 3, 2014, https://www.britishcycling.org.uk/campaigning/article/20141103-campaigning-news-Boardman--Why-I-didn-t-wear-a-helmet-on-BBC-Breakfast-0. 5 Nick Hussey, “Why My Cycling Clothing Company Uses Models without Helmets,” The Guardian, February 4, 2016, https://www.theguardian.com/environment/bike-blog/2016/feb/04/vulpine-bike-clothing-company-models-without-helmets-dont-hate-us. 6 Peter Jacobsen and Harry Rutter, “Cycling Safety,” in Pucher and Buehler, City Cycling, ch. 7. 7 “Helmets for Pedal Cyclists and for Users of Skateboards and Roller Skates,” European Committee for Standardization, 1997, http://www.mrtn.ch/pdf/en_1078.pdf. 8 R.G. Attewell, K. Glase, and M. McFadden, “Bicycle Helmet Efficacy: A Meta-Analysis,” Accident Analysis and Prevention 33 (2001). 9 Rune Elvik, “Publication bias and time-trend bias in meta-analysis of bicycle helmet efficacy: A re-analysis of Attewell, Glase and McFadden,” Accident Analysis and Prevention 43 (2011):1245–51. 10 E-mail exchange with the author. 11 Davis, Death on the Streets. 12 1985 Durbin-Harvey report, commissioned by UK Department of Transport from two professors of statistics. 13 Ian Walker, “Drivers Overtaking Bicyclists: Objective Data on the Effects of Riding Position, Helmet Use, Vehicle Type and Apparent Gender,” Accident Analysis and Prevention 39 (2007):417–25. 14 “Wearing a Helmet Puts Cyclists at Risk, Suggests Research,” University of Bath, September 11, 2016, http://www.bath.ac.uk/news/articles/archive/overtaking110906.html. 15 Tim Gamble and Ian Walker, “Wearing a Bicycle Helmet Can Increase Risk Taking and Sensation Seeking in Adults,” Psychological Science, 2016. 16 “Helmet Wearing Increases Risk Taking and Sensation Seeking,” University of Bath, January 25, 2016, http://www.bath.ac.uk/news/2016/01/25/helmet-wearing-risk-taking. 17 Fishman et al., “Barriers and Facilitators to Public Bicycle Scheme Use: A Qualitative Approach,” Transportation Research Part F: Traffic Psychology and Behaviour 15, Vol. 6 (2012):686–98. 18 Interview with the author. 19 N.C.
Critical: Science and Stories From the Brink of Human Life by Matt Morgan
agricultural Revolution, Atul Gawande, biofilm, Black Swan, Checklist Manifesto, cognitive dissonance, crew resource management, Daniel Kahneman / Amos Tversky, David Strachan, discovery of penicillin, en.wikipedia.org, hygiene hypothesis, job satisfaction, John Snow's cholera map, meta analysis, meta-analysis, personalized medicine, publication bias, randomized controlled trial, Silicon Valley, stem cell, Steve Jobs
For this then to be disseminated, it needs to be published by one of a small number of journals, each with its own tastes, motivations and ties to the pharmaceutical industry. It is estimated that over half of all studies are never completed and data from one-third of trials not published. Of those that are, only half are read by more than just two people. Furthermore, journals are more likely to publish papers with positive results, conducted by well-known groups, by men and from Western countries. This introduces yet more bias, known as publication bias. So, we now have bias squared. It is on this flimsy basis that we decide how to treat patients. This selective publishing should not be acceptable in medicine. The former editor of the British Medical Journal has argued that the entire medical journal industry should be disbanded. The powerful ‘all trials’ movement led by Dr Ben Goldacre aims to publicise these issues surrounding clinical-trial data loss, manipulation and concealment.
The No Need to Diet Book: Become a Diet Rebel and Make Friends With Food by Plantbased Pixie
Most people who embark on a diet try something at home or pay to join a commercial weight-loss programme. Very few of these programmes publish their results and tend to stick to individual anecdotes instead, but the limited research we do have suggests that the largest weight loss was around 3.2 per cent of body weight after two years.9 Are you underwhelmed? ’Cause I sure am. On top of all that, you have to consider publication bias – scientific journals are far more likely to publish a study that shows a significant effect over something that didn’t work. Weight-loss programmes in the workplace and in schools have been equally unsuccessful. Despite appearing to be very concerned about the students’ growing waistlines, very few schools actually assess the impact of making nutritional changes on pupils’ weight. When they do, the results aren’t exactly promising either, as simple techniques like discouraging fizzy drinks have pretty much no effect at all.10 The lack of research in this area allows people to continue to think that school interventions are successful, as there is no published evidence to the contrary.
Grain Brain: The Surprising Truth About Wheat, Carbs, and Sugar--Your Brain's Silent Killers by David Perlmutter, Kristin Loberg
epigenetics, Gary Taubes, Kickstarter, longitudinal study, meta analysis, meta-analysis, microbiome, mouse model, phenotype, publication bias, Ralph Waldo Emerson, selective serotonin reuptake inhibitor (SSRI), stem cell
In 2010, the American Journal of Clinical Nutrition published an astonishing study that revealed the truth behind urban legends about fat, especially the saturated kind, and heart disease.14 The study was a retrospective evaluation of twenty-one previous medical reports involving more than three hundred forty thousand subjects followed from periods of five to twenty-three years. It concluded that “intake of saturated fat was not associated with an increased risk of coronary heart disease, stroke, or cardiovascular disease.” In comparing the lowest to the highest consumption of saturated fat, the actual risk for coronary heart disease was 19 percent lower in the group consuming the highest amount of saturated fat. The authors also stated: “Our results suggested a publication bias, such that studies with significant associations tended to be received more favorably for publication.” What the authors are implying is that when other studies presented conclusions that were more familiar to the mainstream (i.e., fat causes heart disease), not to mention more attractive to Big Pharma, they were more likely to get published. The truth is we thrive on saturated fats. In the words of Michael Gurr, PhD, author of Lipid Biochemistry: An Introduction, “Whatever causes coronary heart disease, it is not primarily a high intake of saturated fatty acids.”15 In a subsequent report from the American Journal of Clinical Nutrition, a panel of leading researchers in the field of nutrition from around the globe clearly stated: “At present there is no clear relation of saturated fatty acid intake to these outcomes [of obesity, cardiovascular disease, incidence of cancer and osteoporosis].”
Phishing for Phools: The Economics of Manipulation and Deception by George A. Akerlof, Robert J. Shiller, Stanley B Resor Professor Of Economics Robert J Shiller
"Robert Solow", Andrei Shleifer, asset-backed security, Bernie Madoff, business cycle, Capital in the Twenty-First Century by Thomas Piketty, collapse of Lehman Brothers, corporate raider, Credit Default Swap, Daniel Kahneman / Amos Tversky, dark matter, David Brooks, desegregation, en.wikipedia.org, endowment effect, equity premium, financial intermediation, financial thriller, fixed income, full employment, George Akerlof, greed is good, income per capita, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kenneth Rogoff, late fees, loss aversion, market bubble, Menlo Park, mental accounting, Milgram experiment, money market fund, moral hazard, new economy, Pareto efficiency, Paul Samuelson, payday loans, Ponzi scheme, profit motive, publication bias, Ralph Nader, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, short selling, Silicon Valley, the new new thing, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, Thorstein Veblen, too big to fail, transaction costs, Unsafe at Any Speed, Upton Sinclair, Vanguard fund, Vilfredo Pareto, wage slave
Gross, “Scope and Impact of Financial Conflicts of Interest in Biomedical Research: A Systematic Review,” Journal of the American Medical Association 289, no. 4 (January 22, 2003): 454–65; Joel Lexchin, Lisa A. Bero, Benjamin Djulbegovic, and Otavio Clark, “Pharmaceutical Industry Sponsorship and Research Outcome and Quality: Systematic Review,” British Medical Journal 326, no. 7400 (May 31, 2003): 1167. Bekelman, Li, and Gross also refer to two studies of “multiple reporting of studies with positive outcomes, further compounding publication bias.” 17. Bob Grant, “Elsevier Published 6 Fake Journals,” The Scientist, May 7, 2009, accessed November 24, 2014, http://classic.the-scientist.com/blog/display/55679/. See also Ben Goldacre, Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients (New York: Faber and Faber/Farrar, Straus and Giroux, 2012), pp. 309–10. 18. Claire Bombardier et al., “Comparison of Upper Gastrointestinal Toxicity of Rofecoxib and Naproxen in Patients with Rheumatoid Arthritis,” New England Journal of Medicine 343, no. 21 (November 23, 2000): 1520–28. 19.
Black Box Thinking: Why Most People Never Learn From Their Mistakes--But Some Do by Matthew Syed
Airbus A320, Alfred Russel Wallace, Arthur Eddington, Atul Gawande, Black Swan, British Empire, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cognitive bias, cognitive dissonance, conceptual framework, corporate governance, creative destruction, credit crunch, crew resource management, deliberate practice, double helix, epigenetics, fear of failure, fundamental attribution error, Henri Poincaré, hindsight bias, Isaac Newton, iterative process, James Dyson, James Hargreaves, James Watt: steam engine, Johannes Kepler, Joseph Schumpeter, Kickstarter, Lean Startup, mandatory minimum, meta analysis, meta-analysis, minimum viable product, publication bias, quantitative easing, randomized controlled trial, selection bias, Shai Danziger, Silicon Valley, six sigma, spinning jenny, Steve Jobs, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, Toyota Production System, US Airways Flight 1549, Wall-E, Yom Kippur War
As Anthony Hidden QC, the man who investigated the Clapham Junction Rail Disaster, which killed thirty-five people in 1988, put it: “There is almost no human action or decision that cannot be made to look flawed and less sensible in the misleading light of hindsight.” *This has a rather obvious analog with what is sometimes called “defensive medicine,” in which clinicians use a host of unnecessary tests that protect their backs, but massively increase health-care costs. *Science is not without flaws, and an eye should always be kept on social and institutional obstacles to progress. Current concerns include publication bias (whereonly successful experiments are published in journals), the weakness of the peer review system, and the fact that many experiments do not appear to be replicable. For a good review of the issues, see: www.economist.com/news/briefing/21588057-scientists-think-self-correcting-alarming-degree-if-not-trouble. *As the creativity researcher Charlan Nemeth has put it: “The presence of dissenting minority views appears to stimulate more originality.”
The Economics Anti-Textbook: A Critical Thinker's Guide to Microeconomics by Rod Hill, Anthony Myatt
American ideology, Andrei Shleifer, Asian financial crisis, bank run, barriers to entry, Bernie Madoff, business cycle, cognitive dissonance, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, different worldview, endogenous growth, equal pay for equal work, Eugene Fama: efficient market hypothesis, experimental economics, failed state, financial innovation, full employment, gender pay gap, Gini coefficient, Gunnar Myrdal, happiness index / gross national happiness, Home mortgage interest deduction, Howard Zinn, income inequality, indoor plumbing, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, liberal capitalism, low skilled workers, market bubble, market clearing, market fundamentalism, Martin Wolf, medical malpractice, minimum wage unemployment, moral hazard, Pareto efficiency, Paul Samuelson, Peter Singer: altruism, positional goods, prediction markets, price discrimination, principal–agent problem, profit maximization, profit motive, publication bias, purchasing power parity, race to the bottom, Ralph Nader, random walk, rent control, rent-seeking, Richard Thaler, Ronald Reagan, shareholder value, The Myth of the Rational Market, the payments system, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, ultimatum game, union organizing, working-age population, World Values Survey, Yogi Berra
These results have been the subject of a ‘lively’ debate, discussed in Card and Krueger’s 1995 book Myth and Measurement.4 Some idea of the tone of the debate can be had by noting that Valentine (1996) accused Card and Krueger (1994) of practising ‘politically correct’ economics, and of deliberately using suspect data in one of their studies. For their part, Card and Krueger present evidence of ‘publication bias’ against results contrary to textbook conventional wisdom (1995: 186). A feature of the debate, key for our discussion of methodology, is that one team of authors would consistently find results different from another team. David Levine, editor of the Berkeley journal Industrial Relations, attributed this phenomenon to ‘author biases’, which he diplomatically defined as ‘conscious or unconscious biases in searching for a robust equation’ (2001: 161).
Fix Your Gut: The Definitive Guide to Digestive Disorders by John Brisson
23andMe, big-box store, biofilm, butterfly effect, clean water, life extension, meta analysis, meta-analysis, microbiome, pattern recognition, publication bias, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Zimmermann PGP
Therefore, a number of further investigations using multi-approaches such as immunhistochemistry, polymerase chain reaction and smears for exploring the presence of H. pylori are required. ” The study even brings up more limitations: “The present study has several limitations. Firstly, the papers identified in our study were limited to those openly published up to Jul 2012; it is possible that some related published or unpublished studies that might meet the inclusion criteria were missed, resulting in any inevitable bias, though the funnel plots and the Egger’s tests failed to show any significant publication bias. Secondly, the results may be interpreted with care because of the limited number and small sample sizes of each included studies. Thirdly, subgroup analyses regarding other confounding factors such as smoking status, age and gender have not been conducted in the present study because sufficient information could not be extracted from the primary literature.” It appears that colonization may be beneficial when it is a part of normal flora.
The White Man's Burden: Why the West's Efforts to Aid the Rest Have Done So Much Ill and So Little Good by William Easterly
airport security, anti-communist, Asian financial crisis, bank run, banking crisis, Bob Geldof, Bretton Woods, British Empire, call centre, clean water, colonial exploitation, colonial rule, Edward Glaeser, end world poverty, European colonialism, failed state, farmers can use mobile phones to check market prices, George Akerlof, Gunnar Myrdal, Hernando de Soto, income inequality, income per capita, Indoor air pollution, invisible hand, Kenneth Rogoff, laissez-faire capitalism, land reform, land tenure, Live Aid, microcredit, moral hazard, Naomi Klein, Nelson Mandela, publication bias, purchasing power parity, randomized controlled trial, Ronald Reagan, Scramble for Africa, structural adjustment programs, The Fortune at the Bottom of the Pyramid, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, War on Poverty, Xiaogang Anhui farmers
For the announcement of the Millennium Challenge Corporation on November 26, 2002, see http://www.whitehouse.gov/news/releases/2002/11/20021126-8.html#3. For the quoted passage on the motivation behind this new aid, see http://www. whitehouse.gov/infocus/developingnations/>. 11.http://www.mca.gov/countries_overview.html. 12.Esther Duflo and Michael Kremer, “Use of Randomization in the Evaluation of Development Effectiveness,” mimeograph, Harvard and MIT (2003), discuss publication bias. A classic paper on this problem is J. Bradford DeLong and Kevin Lang, “Are All Economic Hypotheses False?” Journal of Political Economy 100, no. 6 (December 1992): 1257–72. 13.UN Millennium Project Report, “Investing in Development: A Practical Plan to Achieve the Millennium Development Goals,” overview, box 8, p. 41. 14.Commission for Africa, “Our Common Interest: Report of the Commission for Africa,” p. 348; www.commissionforafrica.org/english/report/introduction.html. 15.Raghuram G.
The Case Against Education: Why the Education System Is a Waste of Time and Money by Bryan Caplan
affirmative action, Affordable Care Act / Obamacare, assortative mating, conceptual framework, correlation does not imply causation, deliberate practice, deskilling, disruptive innovation, en.wikipedia.org, endogenous growth, experimental subject, fear of failure, Flynn Effect, future of work, George Akerlof, ghettoisation, hive mind, job satisfaction, Kenneth Arrow, Khan Academy, labor-force participation, longitudinal study, low skilled workers, market bubble, mass incarceration, meta analysis, meta-analysis, Peter Thiel, price discrimination, profit maximization, publication bias, risk tolerance, Robert Gordon, Ronald Coase, school choice, selection bias, Silicon Valley, statistical model, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, the scientific method, The Wisdom of Crowds, trickle-down economics, twin studies, unpaid internship, upwardly mobile, women in the workforce, yield curve, zero-sum game
“The Romance of College Attendance: Higher Education Stratification and Mate Selection.” Research in Social Stratification and Mobility 26 (2): 107–21. Arum, Richard, and Yossi Shavit. 1995. “Secondary Vocational Education and the Transition from School to Work.” Sociology of Education 68 (3): 187–204. Ashenfelter, Orley, Colm Harmon, and Hessel Oosterbeek. 1999. “A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias.” Labour Economics 6 (4): 453–70. Assaad, Ragui. 1997. “The Effects of Public Sector Hiring and Compensation Policies on the Egyptian Labor Market.” World Bank Economic Review 11 (1): 85–118. Astin, Alexander. 2005–6. “Making Sense out of Degree Completion Rates.” Journal of College Student Retention 7 (1–2): 5–17. ASVAB. 2015. “Test Score Precision.” Accessed November 15. http://official-asvab.com/reliability_res.htm.
The Barbell Prescription: Strength Training for Life After 40 by Jonathon Sullivan, Andy Baker
complexity theory, en.wikipedia.org, epigenetics, experimental subject, Gary Taubes, indoor plumbing, longitudinal study, meta analysis, meta-analysis, moral panic, phenotype, publication bias, randomized controlled trial, selective serotonin reuptake inhibitor (SSRI), the scientific method, Y Combinator
This is not a mere assertion, but a conclusion based on the best evidence we have accumulated over the last twenty or thirty years, and especially since the dawn of the 21st century, when we’ve seen an explosion of research literature on the topic. In this pivotal chapter, we’ll survey some of that evidence. This is as good a time as any to point out an inconvenient truth about published scientific research: Like all other human endeavors, it’s about 90% shit by weight. This has always been true, and if anything it’s even more true now, as research effort is heavily impacted by publication bias, the pressures of academic life, and the corruption of science by industry, which has a decidedly non-scientific axe to grind.2 This sad fact of life does not exempt the biomedical literature,3 whether we’re talking about exercise medicine,4 cancer chemotherapy, diagnostic imaging, or even basic cell bi So I want to be perfectly up front with you: Just as you can easily find studies showing that generally accepted and widely used medical therapies do not actually produce the desired results, so are there contrary findings in the literature on strength training for various disease states and their markers.5 This overview of the literature focuses on the overwhelming preponderance of the evidence, draws heavily on physiological reasoning and experience, and would of necessity involve my own very human biases, whether I admitted it or not.
The Pot Book: A Complete Guide to Cannabis by Julie Holland
Berlin Wall, Burning Man, longitudinal study, Mahatma Gandhi, mandatory minimum, Maui Hawaii, meta analysis, meta-analysis, pattern recognition, phenotype, placebo effect, profit motive, publication bias, RAND corporation, randomized controlled trial, Ronald Reagan, Rosa Parks, Stephen Hawking, University of East Anglia, zero-sum game
Potential confounders were addressed in these studies, including other drug use and the question of early psychotic symptoms (Zammit et al. 2002; Arseneault et al. 2004). However, as Weiser and others have pointed out, a two- to threefold increase in risk is not so sizable and could be explained by unrecognized confounding variables (Weiser and Noy 2005b). Finally, there is also the issue of potential publication bias; negative studies that find no association between an exposure and an outcome may be less likely to be published. Biological Plausibility Biological plausibility lends support to the hypothesis of a causal association. If there is a medical basis for the phenomenon in question, it makes more sense. Cannabinoid receptors are found throughout the brain, especially in regions implicated in schizophrenia, such as the limbic and prefrontal cortices, and also the striatum, where they co-localize with dopamine receptors (Reisine 1994).
Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky
autonomous vehicles, Bernie Madoff, biofilm, blood diamonds, British Empire, Broken windows theory, Brownian motion, car-free, clean water, cognitive dissonance, corporate personhood, corporate social responsibility, Daniel Kahneman / Amos Tversky, delayed gratification, desegregation, different worldview, double helix, Drosophila, Edward Snowden, en.wikipedia.org, epigenetics, Flynn Effect, framing effect, fudge factor, George Santayana, global pandemic, hiring and firing, illegal immigration, impulse control, income inequality, John von Neumann, Loma Prieta earthquake, long peace, longitudinal study, loss aversion, Mahatma Gandhi, meta analysis, meta-analysis, Mohammed Bouazizi, Monkeys Reject Unequal Pay, mouse model, mutually assured destruction, Nelson Mandela, Network effects, out of africa, Peter Singer: altruism, phenotype, placebo effect, publication bias, RAND corporation, risk tolerance, Rosa Parks, selective serotonin reuptake inhibitor (SSRI), self-driving car, Silicon Valley, social intelligence, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steven Pinker, strikebreaker, theory of mind, transatlantic slave trade, traveling salesman, trickle-down economics, twin studies, ultimatum game, Walter Mischel, wikimedia commons, zero-sum game
., “Television Viewing and Aggressive Behavior During Adolescence and Adulthood,” Sci 295 (2002): 2468; J. Savage and C. Yancey, “The Effects of Media Violence Exposure on Criminal Aggression: A Meta-analysis,” Criminal Justice and Behav 35 (2008): 772; C. Anderson et al., “Violent Video Game Effects on Aggression, Empathy, and Prosocial Behavior in Eastern and Western Countries: A Meta-analytic Review,” Psych Bull 136, 151; C. J. Ferguson, “Evidence for Publication Bias in Video Game Violence Effects Literature: A Meta-analytic Review,” Aggression and Violent Behavior 12 (2007): 470; C. Ferguson, “The Good, the Bad and the Ugly: A Meta-analytic Review of Positive and Negative Effects of Violent Video Games,” Psychiatric Quarterly 78 (2007): 309. 42. W. Copeland et al., “Adult Psychiatric Outcomes of Bullying and Being Bullied by Peers in Childhood and Adolescence,” JAMA Psychiatry 70 (2013): 419; S.
Golden Holocaust: Origins of the Cigarette Catastrophe and the Case for Abolition by Robert N. Proctor
bioinformatics, carbon footprint, clean water, corporate social responsibility, Deng Xiaoping, desegregation, facts on the ground, friendly fire, germ theory of disease, global pandemic, index card, Indoor air pollution, information retrieval, invention of gunpowder, John Snow's cholera map, language of flowers, life extension, New Journalism, optical character recognition, pink-collar, Ponzi scheme, Potemkin village, publication bias, Ralph Nader, Ronald Reagan, selection bias, speech recognition, stem cell, telemarketer, Thomas Kuhn: the structure of scientific revolutions, Triangle Shirtwaist Factory, Upton Sinclair, Yogi Berra
Switzer denounced the EPA’s report as highly flawed and “problematic,” peppering his critique with pejoratives like “astonishing,” “equivocal,” “deceptive and pointless,” and “serious difficulties.” The Stanford statistician accused the EPA of imprecision, inconsistency, faulty interpretations, improper extrapolations, use of “crude and disputable” estimates of exposure, bias from confounding and misclassification, improper treatment of publication bias, reliance on inconsistent or improperly recorded data, and several other flaws.39 Switzer was well paid for his services, receiving a total of $647,046 from CIAR and other grants in one two-year period. He was also paid handsomely for private consultations with cartel law firms. In one three-month period in the fall of 1991 he received $26,900 from Covington & Burling for consulting on “health effects of exposure to ETS in the workplace” and an analysis of “epidemiology of spousal smoke exposure and lung cancer.”
Ashes to Ashes: America's Hundred-Year Cigarette War, the Public Health, and the Unabashed Triumph of Philip Morris by Richard Kluger
air freight, Albert Einstein, California gold rush, cognitive dissonance, corporate raider, desegregation, double entry bookkeeping, family office, feminist movement, full employment, ghettoisation, Indoor air pollution, medical malpractice, Mikhail Gorbachev, plutocrats, Plutocrats, publication bias, Ralph Nader, Ralph Waldo Emerson, RAND corporation, rent-seeking, risk tolerance, Ronald Reagan, selection bias, The Chicago School, the scientific method, Torches of Freedom, trade route, transaction costs, traveling salesman, union organizing, upwardly mobile, urban planning, urban renewal, War on Poverty
Public impressions to the contrary, no investigator had produced evidence remotely approaching in strength and consistency findings like those incriminating direct smoking by Wynder, Hammond and Horn, Doll and Hill, and Auerbach. The industry could thus retain the hope that a large-scale study might fail to show a correlation between lung cancer occurrence and exposure to ETS among nonsmokers. Such results, however, might not find their way into scientific journals because of a phenomenon known as “publication bias;” studies that produced negative results or did not report a statistically significant relationship were generally assigned a low priority among submissions. But in the spring of 1990, a Philip Morris scientist, Thomas J. Borelli, who bore the suggestive title of “manager of scientific issues,” was scouring about for unpublished studies on ETS and, while consulting the University Microfilms International Dissertation Information Service, struck gold.