A simulation-based marginal method for longitudinal data with dropout and mismeasured covariates

DOI10.1093/BIOSTATISTICS/KXM054zbMath1143.62067OpenAlexW2170016983WikidataQ31142904 ScholiaQ31142904MaRDI QIDQ146172

Grace Y. Yi, Grace Y. Yi

Publication date: 16 January 2008

Published in: Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biostatistics/kxm054

zbMATH Keywords

longitudinal datameasurement errormissing dataestimating equationssimulation and extrapolation method

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items (4)

Variable selection and inference procedures for marginal analysis of longitudinal data with missing observations and covariate measurement error ⋮ Simultaneous Inference and Bias Analysis for Longitudinal Data with Covariate Measurement Error and Missing Responses ⋮ swgee ⋮ Measurement error correction for the cumulative average model in the survival analysis of nutritional data: application to nurses' health study

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