Estimation and inference for the causal effect of receiving treatment on a multinomial outcome: an alternative approach
- PMID: 20560933
- PMCID: PMC3030650
- DOI: 10.1111/j.1541-0420.2010.01451_1.x
Estimation and inference for the causal effect of receiving treatment on a multinomial outcome: an alternative approach
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.
© 2010, The International Biometric Society No claim to original US government works.
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