Bayesian variable selection in sample selection models using spike-and-slab priors
样本选择模型中的贝叶斯变量选择:spike-and-slab 先验
Sample selection models are a widely used approach for correcting bias caused by data that are missing not at random. Their formulation requires specifying the variables that influence the outcome and those that drive the selection process. This specification is often based on expert knowledge, which can result in the inclusion of irrelevant variables or the omission of important ones. Moreover, to avoid inferential problems such as practical non-identifiability,…