andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2131 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Can we use Bayesian methods to resolve the current crisis of unreplicable research? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. Here are the details, and here are the slides from the last time I gave this talk.
sentIndex sentText sentNum sentScore
1 Can we use Bayesian methods to resolve the current crisis of unreplicable research? [sent-1, score-1.04]
2 In recent years, psychology and medicine have been rocked by scandals of research fraud. [sent-2, score-0.969]
3 At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that cannot be replicated. [sent-3, score-1.74]
4 All this is occurring despite (or perhaps because of? [sent-4, score-0.381]
5 ) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. [sent-5, score-0.957]
6 We consider ways in which prior information and Bayesian methods might help resolve these problems. [sent-6, score-0.938]
7 Here are the details, and here are the slides from the last time I gave this talk. [sent-7, score-0.438]
wordName wordTfidf (topN-words)
[('resolve', 0.351), ('rocked', 0.255), ('scandals', 0.228), ('unreliable', 0.213), ('unreplicable', 0.213), ('awareness', 0.199), ('occurring', 0.177), ('routinely', 0.171), ('restrict', 0.168), ('crisis', 0.167), ('growing', 0.166), ('flaws', 0.166), ('practices', 0.162), ('slides', 0.161), ('research', 0.16), ('methods', 0.157), ('medicine', 0.152), ('bayesian', 0.14), ('despite', 0.136), ('tools', 0.134), ('supposed', 0.131), ('journals', 0.123), ('extent', 0.117), ('publish', 0.116), ('type', 0.115), ('gave', 0.112), ('control', 0.109), ('rate', 0.107), ('details', 0.106), ('psychology', 0.104), ('serious', 0.103), ('top', 0.101), ('current', 0.1), ('claims', 0.1), ('ways', 0.096), ('error', 0.095), ('prior', 0.092), ('scientific', 0.09), ('talk', 0.09), ('help', 0.088), ('time', 0.088), ('consider', 0.083), ('last', 0.077), ('information', 0.071), ('recent', 0.07), ('general', 0.069), ('perhaps', 0.068), ('years', 0.059), ('statistics', 0.057), ('use', 0.052)]
simIndex simValue blogId blogTitle
same-blog 1 1.0000001 2131 andrew gelman stats-2013-12-12-My talk at Leuven, Sat 14 Dec
Introduction: Can we use Bayesian methods to resolve the current crisis of unreplicable research? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. Here are the details, and here are the slides from the last time I gave this talk.
Introduction: The talk is at the University of Amsterdam in the Diamantbeurs (Weesperplein 4, Amsterdam), room 5.01, at noon. Here’s the plan: Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that are implausible and cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. I don’t know how organized this talk will be. It combines a bunch of ideas that have been floating around recently. Here are a few recent articles that
3 0.15166502 2275 andrew gelman stats-2014-03-31-Just gave a talk
Introduction: I just gave a talk in Milan. Actually I was sitting at my desk, it was a g+ hangout which was a bit more convenient for me. The audience was a bunch of astronomers so I figured they could handle a satellite link. . . . Anyway, the talk didn’t go so well. Two reasons: first, it’s just hard to get the connection with the audience without being able to see their faces. Next time I think I’ll try to get several people in the audience to open up their laptops and connect to the hangout, so that I can see a mosaic of faces instead of just a single image from the front of the room. The second problem with the talk was the topic. I asked the people who invited me to choose a topic, and they picked Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? But I don’t think this was right for this audience. I think that it would’ve been better to give them the Stan talk or the little data talk or the statistic
4 0.1484133 1139 andrew gelman stats-2012-01-26-Suggested resolution of the Bem paradox
Introduction: There has been an increasing discussion about the proliferation of flawed research in psychology and medicine, with some landmark events being John Ioannides’s article , “Why most published research findings are false” (according to Google Scholar, cited 973 times since its appearance in 2005), the scandals of Marc Hauser and Diederik Stapel, two leading psychology professors who resigned after disclosures of scientific misconduct, and Daryl Bem’s dubious recent paper on ESP, published to much fanfare in Journal of Personality and Social Psychology, one of the top journals in the field. Alongside all this are the plagiarism scandals, which are uninteresting from a scientific context but are relevant in that, in many cases, neither the institutions housing the plagiarists nor the editors and publishers of the plagiarized material seem to care. Perhaps these universities and publishers are more worried about bad publicity (and maybe lawsuits, given that many of the plagiarism cas
5 0.13658014 1695 andrew gelman stats-2013-01-28-Economists argue about Bayes
Introduction: Robert Bell pointed me to this post by Brad De Long on Bayesian statistics, and then I also noticed this from Noah Smith, who wrote: My impression is that although the Bayesian/Frequentist debate is interesting and intellectually fun, there’s really not much “there” there… despite being so-hip-right-now, Bayesian is not the Statistical Jesus. I’m happy to see the discussion going in this direction. Twenty-five years ago or so, when I got into this biz, there were some serious anti-Bayesian attitudes floating around in mainstream statistics. Discussions in the journals sometimes devolved into debates of the form, “Bayesians: knaves or fools?”. You’d get all sorts of free-floating skepticism about any prior distribution at all, even while people were accepting without question (and doing theory on) logistic regressions, proportional hazards models, and all sorts of strong strong models. (In the subfield of survey sampling, various prominent researchers would refuse to mode
6 0.12301236 371 andrew gelman stats-2010-10-26-Musical chairs in econ journals
7 0.1165567 1878 andrew gelman stats-2013-05-31-How to fix the tabloids? Toward replicable social science research
8 0.11192267 2245 andrew gelman stats-2014-03-12-More on publishing in journals
9 0.11102872 1712 andrew gelman stats-2013-02-07-Philosophy and the practice of Bayesian statistics (with all the discussions!)
10 0.10641526 1844 andrew gelman stats-2013-05-06-Against optimism about social science
11 0.10591824 676 andrew gelman stats-2011-04-23-The payoff: $650. The odds: 1 in 500,000.
12 0.10575053 2093 andrew gelman stats-2013-11-07-I’m negative on the expression “false positives”
13 0.10488707 1149 andrew gelman stats-2012-02-01-Philosophy of Bayesian statistics: my reactions to Cox and Mayo
14 0.10472824 1928 andrew gelman stats-2013-07-06-How to think about papers published in low-grade journals?
15 0.1043345 1435 andrew gelman stats-2012-07-30-Retracted articles and unethical behavior in economics journals?
16 0.10195184 2034 andrew gelman stats-2013-09-23-My talk Tues 24 Sept at 12h30 at Université de Technologie de Compiègne
17 0.098016329 1554 andrew gelman stats-2012-10-31-It not necessary that Bayesian methods conform to the likelihood principle
18 0.097259566 1155 andrew gelman stats-2012-02-05-What is a prior distribution?
19 0.096054211 1779 andrew gelman stats-2013-03-27-“Two Dogmas of Strong Objective Bayesianism”
20 0.095695294 1965 andrew gelman stats-2013-08-02-My course this fall on l’analyse bayésienne de données
topicId topicWeight
[(0, 0.154), (1, 0.044), (2, -0.103), (3, -0.045), (4, -0.114), (5, -0.01), (6, -0.049), (7, 0.004), (8, -0.096), (9, -0.019), (10, 0.022), (11, -0.018), (12, 0.005), (13, 0.041), (14, 0.03), (15, -0.018), (16, 0.006), (17, -0.0), (18, -0.004), (19, 0.031), (20, -0.051), (21, 0.03), (22, 0.025), (23, -0.016), (24, -0.048), (25, -0.017), (26, -0.049), (27, -0.066), (28, 0.033), (29, -0.044), (30, 0.013), (31, 0.037), (32, 0.004), (33, -0.0), (34, 0.054), (35, -0.033), (36, 0.012), (37, 0.009), (38, -0.026), (39, -0.021), (40, -0.002), (41, 0.022), (42, -0.005), (43, -0.006), (44, -0.036), (45, 0.043), (46, 0.022), (47, 0.007), (48, -0.003), (49, 0.055)]
simIndex simValue blogId blogTitle
same-blog 1 0.96619642 2131 andrew gelman stats-2013-12-12-My talk at Leuven, Sat 14 Dec
Introduction: Can we use Bayesian methods to resolve the current crisis of unreplicable research? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. Here are the details, and here are the slides from the last time I gave this talk.
2 0.7267822 2034 andrew gelman stats-2013-09-23-My talk Tues 24 Sept at 12h30 at Université de Technologie de Compiègne
Introduction: Philosophie et practique de la statistique bayésienne . I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. P.S. For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). {\em British Journal of Mathematical and Statistical Psychology} {\bf 66}, 8–18. (Andrew Gelman and Cosma Shalizi) [2013] Rejoinder to discussion. (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should)
3 0.68517655 2000 andrew gelman stats-2013-08-28-Why during the 1950-1960′s did Jerry Cornfield become a Bayesian?
Introduction: Joel Greenhouse writes: I saw your recent paper on Feller [see here and, for a more fanciful theory, here ]. Looks like it was fun to write. I recently wrote a paper that asks an orthogonal question to yours. Why during the 1950-1960′s did Jerry Cornfield become a Bayesian? It appeared in Statistics in Medicine – “On becoming a Bayesian: Early correspondences between J. Cornfield and L. J. Savage.” In his paper, Greenhouse writes: Jerome Cornfield was arguably the leading proponent for the use of Bayesian methods in biostatistics during the 1960s. Prior to 1963, however, Cornfield had no publications in the area of Bayesian statistics. At a time when frequentist methods were the dominant influence on statistical practice, Cornfield went against the mainstream and embraced Bayes. . . . Cornfield’s interest in Bayesian methods began prior to 1961 and that the clarity of his Bayesian outlook began to take shape following Birnbaum’s ASA paper on the likelihood prin- cip
Introduction: Are women three times more likely to wear red or pink when they are most fertile? No, probably not. But here’s how hardworking researchers, prestigious scientific journals, and gullible journalists have been fooled into believing so. The paper I’ll be talking about appeared online this month in Psychological Science, the flagship journal of the Association for Psychological Science, which represents the serious, research-focused (as opposed to therapeutic) end of the psychology profession. . . . In focusing on this (literally) colorful example, I don’t mean to be singling out this particular research team for following what are, unfortunately, standard practices in experimental research. Indeed, that this article was published in a leading journal is evidence that its statistical methods were considered acceptable. Statistics textbooks do warn against multiple comparisons, but there is a tendency for researchers to consider any given comparison alone without considering it as one o
Introduction: The talk is at the University of Amsterdam in the Diamantbeurs (Weesperplein 4, Amsterdam), room 5.01, at noon. Here’s the plan: Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that are implausible and cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. I don’t know how organized this talk will be. It combines a bunch of ideas that have been floating around recently. Here are a few recent articles that
6 0.65807873 205 andrew gelman stats-2010-08-13-Arnold Zellner
7 0.64914411 932 andrew gelman stats-2011-09-30-Articles on the philosophy of Bayesian statistics by Cox, Mayo, Senn, and others!
8 0.64385784 746 andrew gelman stats-2011-06-05-An unexpected benefit of Arrow’s other theorem
9 0.64297193 114 andrew gelman stats-2010-06-28-More on Bayesian deduction-induction
10 0.63781738 2368 andrew gelman stats-2014-06-11-Bayes in the research conversation
11 0.63055611 449 andrew gelman stats-2010-12-04-Generalized Method of Moments, whatever that is
12 0.63048267 1157 andrew gelman stats-2012-02-07-Philosophy of Bayesian statistics: my reactions to Hendry
13 0.62694418 1151 andrew gelman stats-2012-02-03-Philosophy of Bayesian statistics: my reactions to Senn
14 0.62656409 1139 andrew gelman stats-2012-01-26-Suggested resolution of the Bem paradox
15 0.62650192 1712 andrew gelman stats-2013-02-07-Philosophy and the practice of Bayesian statistics (with all the discussions!)
16 0.62261289 1779 andrew gelman stats-2013-03-27-“Two Dogmas of Strong Objective Bayesianism”
17 0.61648792 133 andrew gelman stats-2010-07-08-Gratuitous use of “Bayesian Statistics,” a branding issue?
18 0.61529797 193 andrew gelman stats-2010-08-09-Besag
19 0.61197895 2254 andrew gelman stats-2014-03-18-Those wacky anti-Bayesians used to be intimidating, but now they’re just pathetic
20 0.61197239 1571 andrew gelman stats-2012-11-09-The anti-Bayesian moment and its passing
topicId topicWeight
[(10, 0.029), (15, 0.057), (16, 0.18), (24, 0.029), (40, 0.023), (47, 0.121), (53, 0.022), (62, 0.051), (63, 0.025), (72, 0.043), (82, 0.035), (99, 0.268)]
simIndex simValue blogId blogTitle
same-blog 1 0.95486701 2131 andrew gelman stats-2013-12-12-My talk at Leuven, Sat 14 Dec
Introduction: Can we use Bayesian methods to resolve the current crisis of unreplicable research? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. Here are the details, and here are the slides from the last time I gave this talk.
Introduction: Adam Marcus at Retraction Watch reports on a physicist at the University of Toronto who had this unfortunate thing happen to him: This article has been retracted at the request of the Editor-in-Chief and first and corresponding author. The article was largely a duplication of a paper that had already appeared in ACS Nano, 4 (2010) 3374–3380, http://dx.doi.org/10.1021/nn100335g. The first and the corresponding authors (Kramer and Sargent) would like to apologize for this administrative error on their part . . . “Administrative error” . . . I love that! Is that what the robber says when he knocks over a liquor store and gets caught? As Marcus points out, the two papers have different titles and a different order of authors, which makes it less plausible that this was an administrative mistake (as could happen, for example, if a secretary was given a list of journals to submit the paper to, and accidentally submitted it to the second journal on the list without realizing it
3 0.90103781 1928 andrew gelman stats-2013-07-06-How to think about papers published in low-grade journals?
Introduction: We’ve had lots of lively discussions of fatally-flawed papers that have been published in top, top journals such as the American Economic Review or the Journal of Personality and Social Psychology or the American Sociological Review or the tabloids . And we also know about mistakes that make their way into mid-ranking outlets such as the Journal of Theoretical Biology. But what about results that appear in the lower tier of legitimate journals? I was thinking about this after reading a post by Dan Kahan slamming a paper that recently appeared in PLOS-One. I won’t discuss the paper itself here because that’s not my point. Rather, I had some thoughts regarding Kahan’s annoyance that a paper with fatal errors was published at all. I commented as follows: Read between the lines. The paper originally was released in 2009 and was published in 2013 in PLOS-One, which is one step above appearing on Arxiv. PLOS-One publishes some good things (so does Arxiv) but it’s the place
4 0.89475274 1022 andrew gelman stats-2011-11-21-Progress for the Poor
Introduction: Lane Kenworthy writes : The book is full of graphs that support the above claims. One thing I like about Kenworthy’s approach is that he performs a separate analysis to examine each of his hypotheses. A lot of social scientists seem to think that the ideal analysis will conclude with a big regression where each coefficient tells a story and you can address all your hypotheses by looking at which predictors and interactions have statistically significant coefficients. Really, though, I think you need a separate analysis for each causal question (see chapters 9 and 10 of my book with Jennifer, follow this link ). Kenworthy’s overall recommendation is to increase transfer payments to low-income families and to increase overall government spending on social services, and to fund this through general tax increases. What will it take for this to happen? After a review of the evidence from economic trends and opinion polls, Kenworthy writes, “Americans are potentially recepti
5 0.8910718 321 andrew gelman stats-2010-10-05-Racism!
Introduction: Last night I spoke at the Columbia Club of New York, along with some of my political science colleagues, in a panel about politics, the economy, and the forthcoming election. The discussion was fine . . . until one guy in the audience accused us of bias based on what he imputed as our ethnicity. One of the panelists replied by asking the questioner what of all the things we had said was biased, and the questioner couldn’t actually supply any examples. It makes sense that the questioner couldn’t come up with a single example of bias on our part, considering that we were actually presenting facts . At some level, the questioner’s imputation of our ethnicity and accusation of bias isn’t so horrible. When talking with my friends, I engage in casual ethnic stereotyping all the time–hey, it’s a free country!–and one can certainly make the statistical argument that you can guess people’s ethnicities from their names, appearance, and speech patterns, and in turn you can infer a lot
6 0.89083821 1495 andrew gelman stats-2012-09-13-Win $5000 in the Economist’s data visualization competition
8 0.88681328 1168 andrew gelman stats-2012-02-14-The tabloids strike again
10 0.88161314 95 andrew gelman stats-2010-06-17-“Rewarding Strivers: Helping Low-Income Students Succeed in College”
11 0.88046253 960 andrew gelman stats-2011-10-15-The bias-variance tradeoff
12 0.87897122 1156 andrew gelman stats-2012-02-06-Bayesian model-building by pure thought: Some principles and examples
13 0.8787871 1712 andrew gelman stats-2013-02-07-Philosophy and the practice of Bayesian statistics (with all the discussions!)
14 0.87690008 159 andrew gelman stats-2010-07-23-Popular governor, small state
15 0.87457824 1025 andrew gelman stats-2011-11-24-Always check your evidence
16 0.87452877 1598 andrew gelman stats-2012-11-30-A graphics talk with no visuals!
17 0.87326056 609 andrew gelman stats-2011-03-13-Coauthorship norms
18 0.87257063 700 andrew gelman stats-2011-05-06-Suspicious pattern of too-strong replications of medical research
19 0.87031317 445 andrew gelman stats-2010-12-03-Getting a job in pro sports… as a statistician
20 0.87006891 1143 andrew gelman stats-2012-01-29-G+ > Skype