Andrew & All about that Bayes!


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.

2 Responses to “Andrew & All about that Bayes!”

  1. Do you know if this talk is going to be streamed online, and if so, could you please share with us the link?

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