Xi'an's Og

Andrew Gelman is giving a talk on 11 October at 2 p.m. in Campus Pierre et Marie Curie (Sorbonne Université), room 16-26-209. He will talk about

Prior distribution for causal inference

In Bayesian inference, we must specify a model for the data (a likelihood) and a model for parameters (a prior). Consider two questions:

1. Why is it more complicated to specify the likelihood than the prior?
2. In order to specify the prior, how could can we switch between the theoretical literature (invariance, normality assumption, …) and the applied literature (experts elicitation, robustness, …)?

I will discuss those question in the domain of causal inference: prior distributions for causal effects, coefficients of regression and the other parameters in causal models.

This entry was posted on October 6, 2022 at 12:22 am and is filed under Books, Kids, pictures, Statistics, Travel, University life with tags All about that Bayes, Andrew Gelman, Bayesian Analysis, Bayesian robustness, Campus Pierre et Marie Curie, causal inference, Paris, Place Jussieu, seminar, Sorbonne Université. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.