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Updated: Jun 12, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Estimation and inference for the causal effect of receiving treatment on a multinomial outcome: an alternative
1Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, EPN 3131, 6130 Executive Blvd MSC 7354, Bethesda, Maryland 20892-7354, USA. sb16i@nih.gov
Abstract:
Recently, Cheng (2009, Biometrics 65, 96-103) proposed a model for the causal effect of receiving treatment when there is all-or-none compliance in one randomization group, with maximum likelihood estimation based on convex programming. We discuss an alternative approach that involves a model for all-or-none compliance in two randomization groups and estimation via a perfect fit or an expectation-maximization algorithm for count data. We believe this approach is easier to implement, which would facilitate the reproduction of calculations.
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