andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-507 knowledge-graph by maker-knowledge-mining
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Introduction: A colleague recently sent me a copy of some articles on the estimation of treatment interactions (a topic that’s interested me for awhile). One of the articles, which appeared in the Lancet in 2000, was called “ Subgroup analysis and other (mis)uses of baseline data in clinical trials ,” by Susan F. Assmann, Stuart J. Pocock, Laura E. Enos, and Linda E. Kasten. . . . Hey, wait a minute–I know Susan Assmann! Well, I sort of know her. When I was a freshman in college, I asked my adviser, who was an applied math prof, if I could do some research. He connected me to Susan, who was one of his Ph.D. students, and she gave me a tiny part of her thesis to work on. The problem went as follows. You have a function f(x), for x going from 0 to infinity, that is defined as follows. Between 0 and 1, f(x)=x. Then, for x higher than 1, f’(x) = f(x) – f(x-1). The goal is to figure out what f(x) does. I think I’m getting this right here, but I might be getting confused on some of the detai
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1 A colleague recently sent me a copy of some articles on the estimation of treatment interactions (a topic that’s interested me for awhile). [sent-1, score-0.299]
2 When I was a freshman in college, I asked my adviser, who was an applied math prof, if I could do some research. [sent-12, score-0.183]
3 students, and she gave me a tiny part of her thesis to work on. [sent-15, score-0.158]
4 You have a function f(x), for x going from 0 to infinity, that is defined as follows. [sent-17, score-0.102]
5 The original form of the problem had some sort of probability interpretation, I think–something to do with a one-dimensional packing problem, maybe f(x) was the expected number of objects that would fit in an interval of size x, if the objects were drawn from a uniform distribution. [sent-22, score-0.505]
6 One of the fun things about attacking this sort of problem as a freshman is that I knew nothing about the literature on this sort of problem or even what it was called (a differential-difference equation, or it can also be formulated using as an integral). [sent-24, score-0.838]
7 First I figured out the function in the range [1,2], [2,3], and so forth, then I made a graph (pencil on graph paper) and conjectured the asymptotic behavior of f. [sent-27, score-0.394]
8 I worked on the problem on and off for about eleven months, then one day I finally did it: I had carefully proved the behavior of my function! [sent-30, score-0.276]
9 This accomplishment gave me a warm feeling for years after. [sent-31, score-0.133]
10 I never actually told Susan Assmann about this–I think that by then she had graduated, and I never found out whether she figured out the problem herself as part of her Ph. [sent-32, score-0.534]
11 thesis or whether it was never really needed in the first place. [sent-34, score-0.244]
12 (He was a funny guy: extremely friendly to everyone, including his freshman advisees, but one time we were in his office when he took a phone call. [sent-36, score-0.413]
13 ” After this I never knew whether to trust the guy. [sent-38, score-0.268]
14 If he was that nice to some asshole on the phone, what did it mean that he was nice to us? [sent-39, score-0.214]
15 the new adviser was much nicer–I knew him because I’d taken a class with him–but it didn’t really matter since he was just another mathematician. [sent-41, score-0.245]
16 Anyway, it was funny to see that name–Susan Assmann! [sent-43, score-0.077]
17 They discuss the futility of subgroup analysis given that, compared to main effects, interactions are typically (a) smaller in magnitude and (b) estimated with larger standard errors. [sent-51, score-0.42]
18 (I made a similar argument in a 2001 article in Biostatistics, except that my article went in depth for one particular model and Assmann et al. [sent-53, score-0.219]
19 ) Ultimately I do think treatment interactions and subgroup analysis are important, but they should be estimated using multilevel models. [sent-56, score-0.486]
20 If you try to estimate complex interactions using significance tests or classical interval estimation, you’ll probably just be wasting your time, for reasons explained by Assmann et al. [sent-57, score-0.346]
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Introduction: A colleague recently sent me a copy of some articles on the estimation of treatment interactions (a topic that’s interested me for awhile). One of the articles, which appeared in the Lancet in 2000, was called “ Subgroup analysis and other (mis)uses of baseline data in clinical trials ,” by Susan F. Assmann, Stuart J. Pocock, Laura E. Enos, and Linda E. Kasten. . . . Hey, wait a minute–I know Susan Assmann! Well, I sort of know her. When I was a freshman in college, I asked my adviser, who was an applied math prof, if I could do some research. He connected me to Susan, who was one of his Ph.D. students, and she gave me a tiny part of her thesis to work on. The problem went as follows. You have a function f(x), for x going from 0 to infinity, that is defined as follows. Between 0 and 1, f(x)=x. Then, for x higher than 1, f’(x) = f(x) – f(x-1). The goal is to figure out what f(x) does. I think I’m getting this right here, but I might be getting confused on some of the detai
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Introduction: Susan points me to this . But I don’t really see the point. Simply leaning the bike against the wall seems like a better option to me.
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Introduction: Scott Berry, Brad Carlin, Jack Lee, and Peter Muller recently came out with a book with the above title. The book packs a lot into its 280 pages and is fun to read as well (even if they do use the word “modalities” in their first paragraph, and later on they use the phrase “DIC criterion,” which upsets my tidy, logical mind). The book starts off fast on page 1 and never lets go. Clinical trials are a big part of statistics and it’s cool to see the topic taken seriously and being treated rigorously. (Here I’m not talking about empty mathematical rigor (or, should I say, “rigor”), so-called optimal designs and all that, but rather the rigor of applied statistics, mapping models to reality.) Also I have a few technical suggestions. 1. The authors fit a lot of models in Bugs, which is fine, but they go overboard on the WinBUGS thing. There’s WinBUGS, OpenBUGS, JAGS: they’re all Bugs recommend running Bugs from R using the clunky BRugs interface rather than the smoother bugs(
Introduction: In my article about implausible p-values in psychology studies, I wrote: “Women Are More Likely to Wear Red or Pink at Peak Fertility,” by Alec Beall and Jessica Tracy, is based on two samples: a self-selected sample of 100 women from the Internet, and 24 undergraduates at the University of British Columbia. . . . [There is a problem with] representativeness. What color clothing you wear has a lot to do with where you live and who you hang out with. Participants in an Internet survey and University of British Columbia students aren’t particularly representative of much more than … participants in an Internet survey and University of British Columbia students. In response, I received this in an email from a prominent psychology researcher (not someone I know personally): Complaining that subjects in an experiment were not randomly sampled is what freshmen do before they take their first psychology class. I really *hope* you why that is an absurd criticism – especially of au
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Introduction: Hal Pashler wrote in about a recent paper , “Labor Market Returns to Early Childhood Stimulation: a 20-year Followup to an Experimental Intervention in Jamaica,” by Paul Gertler, James Heckman, Rodrigo Pinto, Arianna Zanolini, Christel Vermeerch, Susan Walker, Susan M. Chang, and Sally Grantham-McGregor. Here’s Pashler: Dan Willingham tweeted: @DTWillingham: RCT from Jamaica: Big effects 20 years later of intervention—teaching parenting/child stimulation to moms in poverty http://t.co/rX6904zxvN Browsing pp. 4 ff, it seems the authors are basically saying “hey the stats were challenging, the sample size tiny, other problems, but we solved them all—using innovative methods of our own devising!—and lo and behold, big positive results!”. So this made me think (and tweet) basically that I hope the topic (which is pretty important) will happen to interest Andy Gelman enough to incline him to give us his take. If you happen to have time and interest… My reply became this artic
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Introduction: Matt Taibbi writes : Glenn Hubbard, Leading Academic and Mitt Romney Advisor, Took $1200 an Hour to Be Countrywide’s Expert Witness . . . Hidden among the reams of material recently filed in connection with the lawsuit of monoline insurer MBIA against Bank of America and Countrywide is a deposition of none other than Columbia University’s Glenn Hubbard. . . . Hubbard testified on behalf of Countrywide in the MBIA suit. He conducted an “analysis” that essentially concluded that Countrywide’s loans weren’t any worse than the loans produced by other mortgage originators, and that therefore the monstrous losses that investors in those loans suffered were due to other factors related to the economic crisis – and not caused by the serial misrepresentations and fraud in Countrywide’s underwriting. That’s interesting, because I worked on the other side of this case! I was hired by MBIA’s lawyers. It wouldn’t be polite of me to reveal my consulting rate, and I never actually got depose
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Introduction: Gregory Eady writes: I’m working on a paper examining the effect of superpower alliance on a binary DV (war). I hypothesize that the size of the effect is much higher during the Cold War than it is afterwards. I’m going to run a Chow test to check whether this effect differs significantly between 1960-1989 and 1990-2007 (Scott Long also has a method using predicted probabilities), but I’d also like to show the trend graphically, and thought that your “Secret Weapon” would be useful here. I wonder if there is anything I should be concerned about when doing this with a (rare-events) logistic regression. I was thinking to graph the coefficients in 5-year periods, moving a single year at a time (1960-64, 1961-65, 1962-66, and so on), reporting the coefficient in the graph for the middle year of each 5-year range). My reply: I don’t know nuthin bout no Chow test but, sure, I’d think the secret weapon would work. If you’re analyzing 5-year periods, it might be cleaner just to keep t
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