Structural Inference in Transition Measurement Error Models for Longitudinal Data

DOI10.1111/j.1541-0420.2005.00446.xzbMath1097.62098OpenAlexW1996826639WikidataQ31055291 ScholiaQ31055291MaRDI QIDQ5492078

Donglin Zeng, Xihong Lin, Wenqin Pan

Publication date: 12 October 2006

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/harvardbiostat/paper51

zbMATH Keywords

EM algorithmasymptotic biasmaximum likelihood estimatormeasurement errortransitional modelsstructrual modeling

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Monte Carlo methods (65C05) Estimation in survival analysis and censored data (62N02)

Related Items

Estimation in Semiparametric Transition Measurement Error Models for Longitudinal Data

Cites Work

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• A General Approach to Analyzing Epidemiologic Data that Contain Misclassification Errors
• Incorporating measurement error in the estimation of autoregressive models for longitudinal data
• Bias Analysis and SIMEX Approach in Generalized Linear Mixed Measurement Error Models
• An EM Algorithm Fitting First-Order Conditional Autoregressive Models to Longitudinal Data
• Frequentist Model Average Estimators
• Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS

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