Identifiability of models for clinical trials with noncompliance

Tianfa Xie; Zhong-Zhan Zhang

doi:10.3934/dcdsb.2004.4.805

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2004, Volume 4, Issue 3: 805-811. Doi: 10.3934/dcdsb.2004.4.805

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Identifiability of models for clinical trials with noncompliance

Tianfa Xie^1, and
Zhong-Zhan Zhang^2,

1.
Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100081
2.
Department of Applied Mathematics, Beijing University of Technology, Beijing 100022

Received: October 31, 2002

Revised: November 30, 2003

Published: July 2005

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Abstract

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.

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Mathematics Subject Classification: 61G05, 95C50.

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