Mixtures of Varying Coefficient Models for Longitudinal Data with Discrete or Continuous Nonignorable Dropout

DOI10.1111/j.0006-341X.2004.00240.xzbMath1274.62790OpenAlexW2046781614WikidataQ30978747 ScholiaQ30978747MaRDI QIDQ3445323

Joseph W. Hogan, Xihong Lin, Benjamin Herman

Publication date: 11 June 2007

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.0006-341x.2004.00240.x

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Comments on: Missing data methods in longitudinal studies: a review., A Brief Review of Approaches to Non‐ignorable Non‐response, Bayesian modeling longitudinal dyadic data with nonignorable dropout, with application to a breast cancer study, Varying-coefficient models for longitudinal processes with continuous-time informative dropout, A marginalized conditional linear model for longitudinal binary data when informative dropout occurs in continuous time, Empirical likelihood inference in mixture of semiparametric varying-coefficient models for longitudinal data with non-ignorable dropout, Mixtures of semiparametric varying coefficient models for longitudinal data with nonignorable dropout, A review on joint models in biometrical research, Empirical likelihood inference in mixtures of semiparametric varying coefficient EV models for longitudinal data with nonignorable dropout, A Dirichlet process mixture model for non-ignorable dropout, Mixed‐Effect Hybrid Models for Longitudinal Data with Nonignorable Dropout

Uses Software

• SAS

Cites Work

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