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Archive of posts filed under the Bayesian Statistics category.

“A hard case for Mister P”

Kevin Van Horn sent me an email with the above title (ok, he wrote MRP, but it’s the same idea) and the following content: I’m working on a problem that at first seemed like a clear case where multilevel modeling would be useful. As I’ve dug into it I’ve found that it doesn’t quite fit […]

My courses this fall at Columbia

Stat 6103, Bayesian Data Analysis, TuTh 1-2:30: We’ll be going through the book, section by section. Follow the link to see slides and lecture notes from when I taught this course a couple years ago. This course has a serious workload: each week we have three homework problems, one theoretical, one computational, and one applied. […]

Discussion with Sander Greenland on posterior predictive checks

Sander Greenland is a leading epidemiologist and educator who’s strongly influenced my thinking on hierarchical models by pointing out that often the data do not supply much information for estimating the group-level variance, a problem that can be particularly severe when the number of groups is low. (And, in some sense, the number of groups […]

Estimated effect of early childhood intervention downgraded from 42% to 25%

Last year I came across an article, “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, that claimed that early childhood stimulation raised adult earnings by 42%. At the […]

SciLua 2 includes NUTS

The most recent release of SciLua includes an implementation of Matt’s sampler, NUTS (link is to the final JMLR paper, which is a revision of the earlier arXiv version). According to the author of SciLua, Stefano Peluchetti: Should be quite similar to your [Stan's] implementation with some differences in the adaptation strategy. If you have […]

Stan World Cup update

The other day I fit a simple model to estimate team abilities from World Cup outcomes. I fit the model to the signed square roots of the score differentials, using the square root on the theory that when the game is less close, it becomes more variable. 0. Background As you might recall, the estimated […]

Stan goes to the World Cup

I thought it would be fun to fit a simple model in Stan to estimate the abilities of the teams in the World Cup, then I could post everything here on the blog, the whole story of the analysis from beginning to end, showing the results of spending a couple hours on a data analysis. […]

Chicago alert: Mister P and Stan to be interviewed on WBEZ today (Fri) 3:15pm

Niala Boodho on the Afternoon Shift will be interviewing Yair and me about our age-period-cohort extravaganza which became widely-known after being featured in this cool interactive graph by Amanda Cox in the New York Times. And here’s the interview. The actual paper is called The Great Society, Reagan’s revolution, and generations of presidential voting and […]

“P.S. Is anyone working on hierarchical survival models?”

Someone who wishes to remain anonymous writes: I’m working on building a predictive model (not causal) of the onset of diabetes mellitus using electronic medical records from a semi-panel of HMO patients. The dependent variable is blood glucose level. The unit of analysis is the patient visit to a network doctor or hospitalization in a […]

“Bayes Data Analysis – Author Needed”

The following item came in over the Bayes email list: Hi, My name is Jo Fitzpatrick and I work as an Acquisition Editor for Packt Publishing ( www.packtpub.com ). We recently commissioned a book on Bayesian Data Analysis and I’m currently searching for an author to write this book. You need to have good working […]