Did you know that Stan automatically runs in parallel (and caches compiled models) from R if you do this: source(“http://mc-stan.org/rstan/stan.R”) It’s from Stan core developer Ben Goodrich. This simple line of code has changed my li...

Did you know that Stan automatically runs in parallel (and caches compiled models) from R if you do this: source(“http://mc-stan.org/rstan/stan.R”) It’s from Stan core developer Ben Goodrich. This simple line of code has changed my li...

As a project for Andrew’s Statistical Communication and Graphics graduate course at Columbia, a few of us (Michael Andreae, Yuanjun Gao, Dongying Song, and I) had the goal of giving RStan’s print and plot functions a makeover. We ended up getting a bit carried away and instead we designed a graphical user interface for interactively exploring virtually […] The post Introducing shinyStan appeared first on Statistical Modeling, Causal Inference, and Social Science.

Ben O’Neill writes: I am a fellow Bayesian statistician at the University of New South Wales (Australia). I have enjoyed reading your various books and articles, and enjoyed reading your recent article on The Perceived Absurdity of Bayesian Inference. However, I disagree with your assertion that the “doomsday argument” is non-Bayesian; I think if you read […] The post Bayes and doomsday appeared first on Statistical Modeling, Causal Inference, and Social…

John Carlin, who’s collaborated on some of my recent work on Type S and Type M errors, prepared this presentation for a clinical audience. It might be of interest to some of you. The ideas and some of the examples should be familiar to regular readers of this blog, but it could be useful to […] The post Statistical Significance – Significant Problem? appeared first on Statistical Modeling, Causal Inference,…

Tomi Peltola, Aki Havulinna, Veikko Salomaa, and Aki Vehtari write: This paper describes an application of Bayesian linear survival regression . . . We compare the Gaussian, Laplace and horseshoe shrinkage priors, and find that the last has the best predictive performance and shrinks strong predictors less than the others. . . . And here’s […] The post Bayesian survival analysis with horseshoe priors—in Stan! appeared first on Statistical Modeling,…

I (Bob, not Andrew) am in Australia until April 30. I’ll be giving some Stan-related and some data annotation talks, several of which have yet to be concretely scheduled. I’ll keep this page updated with what I’ll be up to. All of the talks other than summer school will be open to the public (the […] The post Stan Down Under appeared first on Statistical Modeling, Causal Inference, and Social…

Someone publishes some claim, some statistical comparison with “p less than .05″ attached to it. My response is: OK, you see this pattern in the sample. Do you think it holds in the population? Why do I ask this? Why don’t I ask the more standard question: Do you really think this result is statistically […] The post Why I keep talking about “generalizing from sample to population” appeared first…

Erez Shalom writes: It’s election time in Israel and every week several surveys come out trying to predict the ‘mandates’ that each party will get (out of a total of 120). These surveys are historically flakey, and no one takes the ‘sampling error’ they come with seriously, but no one has a good idea of […] The post Total survey error appeared first on Statistical Modeling, Causal Inference, and Social…