Nested Markov Compliance Class Model in the Presence of Time‐Varying Noncompliance

DOI10.1111/J.1541-0420.2008.01113.XzbMath1167.62088OpenAlexW1989640538WikidataQ41948276 ScholiaQ41948276MaRDI QIDQ3636997

Michael R. Elliott, Julia Y. Lin, Thomas R. Ten Have

Publication date: 30 June 2009

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/upennbiostat/art11

zbMATH Keywords

noncompliancehidden Markov modelprincipal stratificationlatent classgeriatric depressionlongitudinal compliance class model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (2)

Bayesian Inference for Sequential Treatments Under Latent Sequential Ignorability ⋮ Partially Hidden Markov Model for Time-Varying Principal Stratification in HIV Prevention Trials

Cites Work

• Bayesian inference for causal effects in randomized experiments with noncompliance
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• Bayesian inference for causal effects: The role of randomization
• Principal Stratification in Causal Inference
• Identification of Causal Effects Using Instrumental Variables
• Bounds on Causal Effects in Three-Arm Trials With Non-Compliance
• An Extended General Location Model for Causal Inferences from Data Subject to Noncompliance and Missing Values
• Longitudinal Nested Compliance Class Model in the Presence of Time-Varying Noncompliance
• Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes
• Inference for the Complier-Average Causal Effect From Longitudinal Data Subject to Noncompliance and Missing Data, With Application to a Job Training Assessment for the Unemployed
• Estimating Equations for a Latent Transit ion Model with Multiple Discrete Indicators
• Latent Class Model Diagnosis
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• Causal Models for Randomized Physician Encouragement Trials in Treating Primary Care Depression
• Methodology for Evaluating a Partially Controlled Longitudinal Treatment Using Principal Stratification, With Application to a Needle Exchange Program
• Parameterization and Bayesian Modeling

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