1. Nested Markov compliance class model in the presence of time-varying noncompliance.
- Author
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Lin JY, Ten Have TR, and Elliott MR
- Subjects
- Algorithms, Computer Simulation, Epidemiologic Research Design, Pattern Recognition, Automated, Regression Analysis, Reproducibility of Results, Risk Assessment methods, Sensitivity and Specificity, Biometry methods, Data Interpretation, Statistical, Longitudinal Studies, Markov Chains, Models, Statistical, Patient Compliance statistics & numerical data, Randomized Controlled Trials as Topic
- Abstract
Summary: We consider a Markov structure for partially unobserved time-varying compliance classes in the Imbens-Rubin (1997, The Annals of Statistics 25, 305-327) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow-ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time-invariant subject-specific compliance principal strata to summarize longitudinal trends of subject-specific time-varying compliance patterns. The principal strata are formed using Markov models that relate current compliance behavior to compliance history. Treatment effects are estimated as intent-to-treat effects within the compliance principal strata.
- Published
- 2009
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