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Academic innovation & the global public research university, James Hilton
Lin, J.Y., T.R. Ten Have, and Michael R. Elliott. 2009. "Nested Markov Compliance Class Model in the Presence of Time-Varying Noncompliance." Biometrics, 65(2): 505-513.
We consider a Markov structure for partially unobserved time-varying compliance classes in the Imbens-Rubin 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.
PMCID: PMC2700859. (Pub Med Central)
Country of focus: United States of America.