Skip to content
Archive of posts filed under the Decision Theory category.

On deck this week

Mon: “Building on theories used to describe magnets, scientists have put together a model that captures something very different . . .” Tues: Questions about “Too Good to Be True” Wed: “The Europeans and Australians were too eager to believe in renal denervation” Thurs: Ethics and statistics Fri: Differences between econometrics and statistics: From varying […]

Open-source tools for running online field experiments

Dean Eckles points me to this cool new tool for experimentation: I [Eckles] just wanted to share that in a collaboration between Facebook and Stanford, we have a new paper out about running online field experiments. One thing this paper does is describe some of the tools we use to design, deploy, and analyze experiments, […]

Just wondering

It would be bad news if a student in the class of Laurence Tribe or Alan Dershowitz or Ian Ayres or Edward Wegman or Matthew Whitaker or Karl Weick or Frank Fischer were to hand in an assignment that is obviously plagiarized copied from another source without attribution. Would the prof have the chutzpah to […]

On deck this week

Mon: “Bayes Data Analysis – Author Needed” Tues: Just wondering Wed: “P.S. Is anyone working on hierarchical survival models?” Thurs: Open-source tools for running online field experiments Fri: Hey—this is a new kind of spam! Sat, Sun: As Chris Hedges would say: That’s the news, and I am outta here!

On deck this week

Mon: Who invented the Metropolis algorithm? Tues: “Who’s bigger”—the new book that ranks every human on Wikipedia—is more like Bill Simmons than Bill James Wed: “Being an informed Bayesian: Assessing prior informativeness and prior–likelihood conflict” Thurs: “The great advantage of the model-based over the ad hoc approach, it seems to me, is that at any […]

Estimating a customer satisfaction regression, asking only a subset of predictors for each person

Someone writes in with an interesting question: I’d like to speak with you briefly to get your thoughts on the imputation of missing data in a new online web-survey technique I’m developing. Our survey uses Split Questionnaire Design. The total number of surveys will vary in length with different customers, but will generally be between […]

Smullyan and the Randomistas

Steve Ziliak wrote in: I thought you might be interested in the following exchanges on randomized trials: Here are a few exchanges on the economics and ethics of randomized controlled trials, reacting to my [Zilliak's] study with Edward R. Teather-Posadas, “The Unprincipled Randomization Principle in Economics and Medicine”. Our study is forthcoming in the Oxford […]

On deck this week

Mon: Smullyan and the Randomistas Tues: Too Linear To Be True: The curious case of Jens Forster Wed: More on those randomistas Thurs: Estimating a customer satisfaction regression, asking only a subset of predictors for each person Fri: Quantifying luck vs. skill in sports Sat, Sun: Hey, it’s summer—time to take the weekends off. Have […]

Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems

Andreas Graefe sends along this paper (with Helmut Kuchenhoff, Veronika Stierle, and Bernhard Riedl) and writes: We summarize prior evidence from the field of economic forecasting and find that the simple average was more accurate than Bayesian model averaging in three of four studies; on average, the error of BMA was 6% higher than the […]

Average predictive comparisons in R: David Chudzicki writes a package!

Here it is: An R Package for Understanding Arbitrary Complex Models As complex models become widely used, it’s more important than ever to have ways of understanding them. Even when a model is built primarily for prediction (rather than primarily as an aid to understanding), we still need to know what it’s telling us. For […]