Causal inference from treatment-control studies having an additional factor with unknown assignment mechanism

2022/02/07 by Nicole E. Pashley, Pashley, Nicole E., Kristen B. Hunter +7
Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.2202.03533

openalex publication_date 2022/02/07 · openalex created_date 2022/05/05 · openalex updated_date 2026/07/28

Abstract

Consider a situation with two treatments, the first of which is randomized but the second is not, and the multifactor version of this. Interest is in treatment effects, defined using standard factorial notation. We define estimators for the treatment effects and explore their properties when there is information about the nonrandomized treatment assignment and when there is no information on the assignment of the nonrandomized treatment. We show when and how hidden treatments can bias estimators and inflate their sampling variances.

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