Analysis of Longitudinal Data with Non-Ignorable Non-Monotone Missing Values

DOI10.1111/1467-9876.00119zbMath0905.62113OpenAlexW2024291119MaRDI QIDQ4216156

David P. Harrington, Andrea B. Troxel, Stuart R. Lipsitz

Publication date: 3 February 1999

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00119

zbMATH Keywords

incomplete datamaximum likelihoodrepeated measurementsMarkov correlationquality-of-life data

Mathematics Subject Classification ID

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

Related Items

Some issues on longitudinal data with nonignorable dropout, a discussion of “Statistical Inference for Nonignorable Missing-Data Problems: A Selective Review” by Niansheng Tang and Yuanyuan Ju, Missing data methods in longitudinal studies: a review, A Brief Review of Approaches to Non‐ignorable Non‐response, Model‐Assisted Regression Estimators for Longitudinal Data with Nonignorable Dropout, Formal and informal model selection with incomplete data, MCMC-based estimation methods for continuous longitudinal data with non-random (non)-monotone missingness, Monte Carlo modified profile likelihood in models for clustered data, Every Missingness not at Random Model Has a Missingness at Random Counterpart with Equal Fit, A reanalysis of a longitudinal scleroderma clinical trial using non-ignorable missingness models, Analysis of longitudinal data with intermittent missing values using the stochastic EM algorithm, Nonignorable dropout models for longitudinal binary data with random effects: an application of Monte Carlo approximation through the Gibbs output, Evaluating Statistical Hypotheses Using Weakly‐Identifiable Estimating Functions, Sensitivity analysis of longitudinal data with intermittent missing values, Adjusting for Nonignorable Missingness When Estimating Generalized Additive Models, Generalized shared-parameter models and missingness at random, Estimation of random-effects model for longitudinal data with nonignorable missingness using Gibbs sampling, Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches, Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach