Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model Criticism for Bayesian Causal Inference   The goal of causal inference is to understand the outcome of alternative
courses of action. However, all causal inference requires assumptions. Such
assumptions can be more influential than in typical tasks for probabilistic
modeling, and testing those assumptions is important to assess the validity of
causal inference. We develop model criticism for Bayesian causal inference,
building on the idea of posterior predictive checks to assess model fit. Our
approach involves decomposing the problem, separately criticizing the model of
treatment assignments and the model of outcomes. Conditioned on the assumption
of unconfoundedness---that the treatments are assigned independently of the
potential outcomes---we show how to check any additional modeling assumption.
Our approach provides a foundation for diagnosing model-based causal
inferences.

31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
1
The categories of this paper are: cs
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom