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Identifiability of models for clinical trials with noncompliance

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  • In this article we focus on clinical trials in which the compliance is measured with random errors, and develop an error-in-variables model for the analysis of the clinical trials. With this model, we separate the efficacy of prescribed treatment from that of the compliance. With additional information correlated with compliance, we prove that the model is identifiable, and get estimators for the parameters of interest, including the parameter reflecting the efficacy of the treatment. Furthermore, we extend the model to stratified populations, and discuss the asymptotic properties of the estimators.
    Mathematics Subject Classification: 61G05, 95C50.


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