ArticleBiometrics2009
Nested Markov compliance class model in the presence of time-varying noncompliance.
Article in Biometrics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A sensitivity analysis approach to principal stratification with a continuous longitudinal intermediate outcome: applications to a cohort stepped wedge trial.Biostatistics (Oxford, England) · 2026Article
- Survivor Average Causal Effects for Continuous Time: A Principal Stratification Approach to Causal Inference With Semicompeting Risks.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Causal inference in longitudinal comparative effectiveness studies with repeated measures of a continuous intermediate variable.Statistics in medicine · 2014Article
- Joint modeling compliance and outcome for causal analysis in longitudinal studies.Statistics in medicine · 2014Article
- Partially hidden Markov model for time-varying principal stratification in HIV prevention trials.Journal of the American Statistical Association · 2012Article
- A tutorial on principal stratification-based sensitivity analysis: application to smoking cessation studies.Clinical trials (London, England) · 2010Article
- Nested Markov compliance class model in the presence of time-varying noncompliance.Biometrics · 2009Article
- Baseline patient characteristics and mortality associated with longitudinal intervention compliance.Statistics in medicine · 2007Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
summaryWe 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.
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Registered trials
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