andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1262 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Updated version of my paper with Xian: The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. I love this stuff.
sentIndex sentText sentNum sentScore
1 Updated version of my paper with Xian: The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. [sent-1, score-1.596]
2 We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. [sent-2, score-1.544]
3 We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. [sent-3, score-1.695]
wordName wordTfidf (topN-words)
[('missionary', 0.254), ('theoreticians', 0.24), ('doomsday', 0.24), ('absurd', 0.221), ('misguided', 0.215), ('misconceptions', 0.209), ('bayesian', 0.198), ('feller', 0.193), ('xian', 0.19), ('aiming', 0.187), ('matched', 0.179), ('perceived', 0.168), ('updated', 0.166), ('coverage', 0.158), ('intellectual', 0.149), ('continuing', 0.146), ('bayesians', 0.143), ('beginning', 0.14), ('analyze', 0.14), ('historical', 0.135), ('obviously', 0.134), ('text', 0.131), ('behind', 0.129), ('merely', 0.128), ('classic', 0.127), ('attitude', 0.124), ('complete', 0.123), ('version', 0.112), ('direction', 0.111), ('nature', 0.11), ('background', 0.11), ('note', 0.105), ('reasons', 0.105), ('love', 0.104), ('stuff', 0.098), ('old', 0.096), ('cases', 0.093), ('among', 0.087), ('examples', 0.087), ('theory', 0.086), ('probability', 0.08), ('several', 0.079), ('various', 0.079), ('wrong', 0.079), ('consider', 0.078), ('methods', 0.074), ('without', 0.066), ('recent', 0.066), ('statistics', 0.053), ('paper', 0.053)]
simIndex simValue blogId blogTitle
same-blog 1 1.0000001 1262 andrew gelman stats-2012-04-12-“Not only defended but also applied”: The perceived absurdity of Bayesian inference
Introduction: Updated version of my paper with Xian: The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. I love this stuff.
2 0.21169414 1571 andrew gelman stats-2012-11-09-The anti-Bayesian moment and its passing
Introduction: Xian and I respond to the four discussants of our paper, “Not only defended but also applied”: The perceived absurdity of Bayesian inference.” Here’s the abstract of our rejoinder : Over the years we have often felt frustration, both at smug Bayesians—in particular, those who object to checking of the fit of model to data, either because all Bayesian models are held to be subjective and thus unquestioned (an odd combination indeed, but that is the subject of another article)—and angry anti-Bayesians who, as we wrote in our article, strain on the gnat of the prior distribution while swallowing the camel that is the likelihood. The present article arose from our memory of a particularly intemperate anti-Bayesian statement that appeared in Feller’s beautiful and classic book on probability theory. We felt that it was worth exploring the very extremeness of Feller’s words, along with similar anti-Bayesian remarks by others, in order to better understand the background underlying contr
3 0.1722815 1781 andrew gelman stats-2013-03-29-Another Feller theory
Introduction: My paper with Christian Robert, “Not Only Defended But Also Applied”: The Perceived Absurdity of Bayesian Inference , was recently published in The American Statistician, along with discussions by Steve Fienberg, Steve Stigler, Deborah Mayo, and Wesley Johnson, and our rejoinder, The Anti-Bayesian Moment and Its Passing . These articles revolved around the question of why the great probabilist William Feller, in his classic book on probability (“Feller, Volume 1,” as it is known), was so intemperately anti-Bayesian. We located Feller’s attitude within a post-WW2 “anti-Bayesian moment” in which Bayesian inference was perceived as a threat to the dominance of non-Bayesian methods, which were mature enough to have solved problems yet new enough to still appear to have limitless promise. Howard Wainer read this. Howard is a friend who has a longstanding interest in the history of statistics and who also has known a lot of important statisticians over the years. Howard writes: O
4 0.14826508 1469 andrew gelman stats-2012-08-25-Ways of knowing
Introduction: In this discussion from last month, computer science student and Judea Pearl collaborator Elias Barenboim expressed an attitude that hierarchical Bayesian methods might be fine in practice but that they lack theory, that Bayesians can’t succeed in toy problems. I posted a P.S. there which might not have been noticed so I will put it here: I now realize that there is some disagreement about what constitutes a “guarantee.” In one of his comments, Barenboim writes, “the assurance we have that the result must hold as long as the assumptions in the model are correct should be regarded as a guarantee.” In that sense, yes, we have guarantees! It is fundamental to Bayesian inference that the result must hold if the assumptions in the model are correct. We have lots of that in Bayesian Data Analysis (particularly in the first four chapters but implicitly elsewhere as well), and this is also covered in the classic books by Lindley, Jaynes, and others. This sort of guarantee is indeed p
5 0.13410309 1610 andrew gelman stats-2012-12-06-Yes, checking calibration of probability forecasts is part of Bayesian statistics
Introduction: Yes, checking calibration of probability forecasts is part of Bayesian statistics. At the end of this post are three figures from Chapter 1 of Bayesian Data Analysis illustrating empirical evaluation of forecasts. But first the background. Why am I bringing this up now? It’s because of something Larry Wasserman wrote the other day : One of the striking facts about [baseball/political forecaster Nate Silver's recent] book is the emphasis the Silver places on frequency calibration. . . . Have no doubt about it: Nate Silver is a frequentist. For example, he says: One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. Out of all the times you said there was a 40 percent chance of rain, how often did rain actually occur? If over the long run, it really did rain about 40 percent of the time, that means your forecasts were well calibrated. I had some discussion with Larry in the comments section of h
6 0.13010293 357 andrew gelman stats-2010-10-20-Sas and R
7 0.12532373 2254 andrew gelman stats-2014-03-18-Those wacky anti-Bayesians used to be intimidating, but now they’re just pathetic
8 0.12051484 1719 andrew gelman stats-2013-02-11-Why waste time philosophizing?
9 0.11629461 1554 andrew gelman stats-2012-10-31-It not necessary that Bayesian methods conform to the likelihood principle
10 0.11421365 1779 andrew gelman stats-2013-03-27-“Two Dogmas of Strong Objective Bayesianism”
11 0.10686141 1438 andrew gelman stats-2012-07-31-What is a Bayesian?
12 0.10189299 117 andrew gelman stats-2010-06-29-Ya don’t know Bayes, Jack
14 0.097346127 1695 andrew gelman stats-2013-01-28-Economists argue about Bayes
15 0.096808054 1151 andrew gelman stats-2012-02-03-Philosophy of Bayesian statistics: my reactions to Senn
16 0.095161602 534 andrew gelman stats-2011-01-24-Bayes at the end
17 0.093970686 291 andrew gelman stats-2010-09-22-Philosophy of Bayes and non-Bayes: A dialogue with Deborah Mayo
18 0.093563184 467 andrew gelman stats-2010-12-14-Do we need an integrated Bayesian-likelihood inference?
19 0.092401043 1280 andrew gelman stats-2012-04-24-Non-Bayesian analysis of Bayesian agents?
20 0.092293203 1560 andrew gelman stats-2012-11-03-Statistical methods that work in some settings but not others
topicId topicWeight
[(0, 0.112), (1, 0.068), (2, -0.089), (3, 0.029), (4, -0.113), (5, 0.008), (6, -0.05), (7, 0.043), (8, 0.032), (9, -0.073), (10, 0.022), (11, -0.053), (12, -0.005), (13, 0.046), (14, 0.051), (15, 0.043), (16, 0.028), (17, 0.02), (18, -0.021), (19, 0.016), (20, -0.001), (21, 0.065), (22, -0.016), (23, 0.002), (24, 0.032), (25, -0.01), (26, -0.012), (27, 0.009), (28, -0.011), (29, -0.037), (30, 0.031), (31, 0.033), (32, 0.021), (33, -0.045), (34, -0.004), (35, -0.048), (36, -0.009), (37, -0.034), (38, 0.002), (39, 0.001), (40, 0.004), (41, -0.012), (42, -0.001), (43, -0.022), (44, 0.045), (45, -0.013), (46, 0.025), (47, 0.036), (48, -0.012), (49, -0.002)]
simIndex simValue blogId blogTitle
same-blog 1 0.98699349 1262 andrew gelman stats-2012-04-12-“Not only defended but also applied”: The perceived absurdity of Bayesian inference
Introduction: Updated version of my paper with Xian: The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. I love this stuff.
2 0.87426955 1259 andrew gelman stats-2012-04-11-How things sound to us, versus how they sound to others
Introduction: Hykel Hosni noticed this bit from the Lindley Prize page of the Society for Bayesan Analysis: Lindley became a great missionary for the Bayesian gospel. The atmosphere of the Bayesian revival is captured in a comment by Rivett on Lindley’s move to University College London and the premier chair of statistics in Britain: “it was as though a Jehovah’s Witness had been elected Pope.” From my perspective, this was amusing (if commonplace): a group of rationalists jocularly characterizing themselves as religious fanatics. And some of this is in response to intense opposition from outsiders (see the Background section here ). That’s my view. I’m an insider, a statistician who’s heard all jokes about religious Bayesians, from Bayesian and non-Bayesian statisticians alike. But Hosni is an outsider, and here’s how he sees the above-quoted paragraph: Research, however, is not a matter of faith but a matter of arguments, which should always be evaluated with the utmost intellec
3 0.87100846 1781 andrew gelman stats-2013-03-29-Another Feller theory
Introduction: My paper with Christian Robert, “Not Only Defended But Also Applied”: The Perceived Absurdity of Bayesian Inference , was recently published in The American Statistician, along with discussions by Steve Fienberg, Steve Stigler, Deborah Mayo, and Wesley Johnson, and our rejoinder, The Anti-Bayesian Moment and Its Passing . These articles revolved around the question of why the great probabilist William Feller, in his classic book on probability (“Feller, Volume 1,” as it is known), was so intemperately anti-Bayesian. We located Feller’s attitude within a post-WW2 “anti-Bayesian moment” in which Bayesian inference was perceived as a threat to the dominance of non-Bayesian methods, which were mature enough to have solved problems yet new enough to still appear to have limitless promise. Howard Wainer read this. Howard is a friend who has a longstanding interest in the history of statistics and who also has known a lot of important statisticians over the years. Howard writes: O
4 0.86613858 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
5 0.83736771 904 andrew gelman stats-2011-09-13-My wikipedia edit
Introduction: The other day someone mentioned my complaint about the Wikipedia article on “Bayesian inference” (see footnote 1 of this article ) and he said I should fix the Wikipedia entry myself. And so I did . I didn’t have the energy to rewrite the whole article–in particular, all of its examples involve discrete parameters, whereas the Bayesian problems I work on generally have continuous parameters, and its “mathematical foundations” section focuses on “independent identically distributed observations x” rather than data y which can have different distributions. It’s just a wacky, unbalanced article. But I altered the first few paragraphs to get rid of the stuff about the posterior probability that a model is true. I much prefer the Scholarpedia article on Bayesian statistics by David Spiegelhalter and Kenneth Rice, but I couldn’t bring myself to simply delete the Wikipedia article and replace it with the Scholarpedia content. Just to be clear: I’m not at all trying to disparage
6 0.82888871 1571 andrew gelman stats-2012-11-09-The anti-Bayesian moment and its passing
7 0.82106233 117 andrew gelman stats-2010-06-29-Ya don’t know Bayes, Jack
8 0.81741697 114 andrew gelman stats-2010-06-28-More on Bayesian deduction-induction
9 0.81728101 1438 andrew gelman stats-2012-07-31-What is a Bayesian?
10 0.81057668 921 andrew gelman stats-2011-09-23-That odd couple, “subjectivity” and “rationality”
11 0.80674428 1610 andrew gelman stats-2012-12-06-Yes, checking calibration of probability forecasts is part of Bayesian statistics
12 0.7908476 2254 andrew gelman stats-2014-03-18-Those wacky anti-Bayesians used to be intimidating, but now they’re just pathetic
13 0.78804594 2368 andrew gelman stats-2014-06-11-Bayes in the research conversation
14 0.78638589 449 andrew gelman stats-2010-12-04-Generalized Method of Moments, whatever that is
15 0.78511369 1205 andrew gelman stats-2012-03-09-Coming to agreement on philosophy of statistics
16 0.78132987 83 andrew gelman stats-2010-06-13-Silly Sas lays out old-fashioned statistical thinking
17 0.78035086 110 andrew gelman stats-2010-06-26-Philosophy and the practice of Bayesian statistics
18 0.76714891 291 andrew gelman stats-2010-09-22-Philosophy of Bayes and non-Bayes: A dialogue with Deborah Mayo
19 0.76551205 890 andrew gelman stats-2011-09-05-Error statistics
20 0.7639671 453 andrew gelman stats-2010-12-07-Biostatistics via Pragmatic and Perceptive Bayes.
topicId topicWeight
[(0, 0.089), (15, 0.074), (16, 0.045), (21, 0.021), (22, 0.026), (23, 0.037), (24, 0.1), (74, 0.101), (82, 0.018), (84, 0.024), (99, 0.348)]
simIndex simValue blogId blogTitle
same-blog 1 0.97805822 1262 andrew gelman stats-2012-04-12-“Not only defended but also applied”: The perceived absurdity of Bayesian inference
Introduction: Updated version of my paper with Xian: The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. I love this stuff.
2 0.94672281 1135 andrew gelman stats-2012-01-22-Advice on do-it-yourself stats education?
Introduction: Dustin Palmer writes: I am a recent graduate looking for a bit of advice. While I took intro classes on math and statistics in my undergraduate degree as a political science major, I find myself university-less and seeking to develop my statistics toolkit. I work for an NGO in the international development field. I think that a solid statistics foundation would offer me not only more career opportunities, but more importantly, a deeper and more nuanced understanding of the processes and problems that interest me. I’m talking about field experiments and practical quantitative and qualitative data analysis. I have plenty of free time, ambition, and enthusiasm to improve this part of my toolbox, but I lack an attachment to an institution and much in the way of financial resources. How would you go about making a concentrated effort at acquiring an understanding of the field and its actual application in something like R or Stata, which I admit to never having used? Perhaps I am
3 0.94600332 2261 andrew gelman stats-2014-03-23-Greg Mankiw’s utility function
Introduction: From 2010 : Greg Mankiw writes (link from Tyler Cowen ): Without any taxes, accepting that editor’s assignment would have yielded my children an extra $10,000. With taxes, it yields only $1,000. In effect, once the entire tax system is taken into account, my family’s marginal tax rate is about 90 percent. Is it any wonder that I [Mankiw] turn down most of the money-making opportunities I am offered? By contrast, without the tax increases advocated by the Obama administration, the numbers would look quite different. I would face a lower income tax rate, a lower Medicare tax rate, and no deduction phaseout or estate tax. Taking that writing assignment would yield my kids about $2,000. I would have twice the incentive to keep working. First, the good news Obama’s tax rates are much lower than Mankiw had anticipated! According to the above quote, his marginal tax rate is currently 80% but threatens to rise to 90%. But, in October 2008, Mankiw calculated that Obama’s
Introduction: Greg Mankiw writes (link from Tyler Cowen ): Without any taxes, accepting that editor’s assignment would have yielded my children an extra $10,000. With taxes, it yields only $1,000. In effect, once the entire tax system is taken into account, my family’s marginal tax rate is about 90 percent. Is it any wonder that I [Mankiw] turn down most of the money-making opportunities I am offered? By contrast, without the tax increases advocated by the Obama administration, the numbers would look quite different. I would face a lower income tax rate, a lower Medicare tax rate, and no deduction phaseout or estate tax. Taking that writing assignment would yield my kids about $2,000. I would have twice the incentive to keep working. First, the good news Obama’s tax rates are much lower than Mankiw had anticipated! According to the above quote, his marginal tax rate is currently 80% but threatens to rise to 90%. But, in October 2008, Mankiw calculated that Obama’s would tax his m
5 0.94538546 1828 andrew gelman stats-2013-04-27-Time-Sharing Experiments for the Social Sciences
Introduction: James Druckman and Jeremy Freese write: We are pleased to announce that Time-Sharing Experiments for the Social Sciences (TESS) was renewed for another round of funding by NSF starting last Fall. TESS allows researchers to submit proposals for experiments to be conducted on a nationally-representative, probability-based Internet platform, and successful proposals are fielded at no cost to investigators. More information about how TESS works and how to submit proposals is available at http://www.tessexperiments.org. Additionally, we are pleased to announce the development of two new proposal mechanisms. TESS’s Short Studies Program (SSP) is accepting proposals for fielding very brief population-based survey experiments on a general population of at least 2000 adults. SSP recruits participants from within the U.S. using the same Internet-based platform as other TESS studies. More information about SSP and proposal requirements is available at http://www.tessexperiments.org/ssp.
6 0.94142258 338 andrew gelman stats-2010-10-12-Update on Mankiw’s work incentives
7 0.94012105 285 andrew gelman stats-2010-09-18-Fiction is not for tirades? Tell that to Saul Bellow!
8 0.93931878 1781 andrew gelman stats-2013-03-29-Another Feller theory
9 0.93603563 836 andrew gelman stats-2011-08-03-Another plagiarism mystery
10 0.93593276 2239 andrew gelman stats-2014-03-09-Reviewing the peer review process?
11 0.93341053 862 andrew gelman stats-2011-08-20-An illustrated calculus textbook
12 0.93243587 1068 andrew gelman stats-2011-12-18-Faculty who don’t like teaching and hate working with students
13 0.93170321 557 andrew gelman stats-2011-02-05-Call for book proposals
14 0.93068075 1177 andrew gelman stats-2012-02-20-Joshua Clover update
15 0.93054402 1085 andrew gelman stats-2011-12-27-Laws as expressive
16 0.92940521 4 andrew gelman stats-2010-04-26-Prolefeed
18 0.92817724 125 andrew gelman stats-2010-07-02-The moral of the story is, Don’t look yourself up on Google
19 0.92723095 1395 andrew gelman stats-2012-06-27-Cross-validation (What is it good for?)
20 0.92574495 1139 andrew gelman stats-2012-01-26-Suggested resolution of the Bem paradox