A test of missing completely at random for generalised estimating equations with missing data

DOI10.1093/biomet/86.1.1zbMath1101.62314OpenAlexW2055596130MaRDI QIDQ4238068

Hua Yun Chen, Roderick J. A. Little

Publication date: 1999

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/86.1.1

zbMATH Keywords

Incomplete dataLongitudinal dataDrop-outMissing-data mechanism.

Mathematics Subject Classification ID

Point estimation (62F10) Generalized linear models (logistic models) (62J12)

Related Items

An application of nonparametric regression to missing data in large market surveys, A hybrid approach for regression analysis with block missing data, A nonparametric test of missing completely at random for incomplete multivariate data, Score Test for Missing at Random or Not under Logistic Missingness Models, Poststratification fusion learning in longitudinal data analysis, Optimal nonparametric testing of missing completely at random and its connections to compatibility, Testing the missing at random assumption in generalized linear models in the presence of instrumental variables, Tests of homogeneity of means and covariance matrices for multivariate incomplete data, A unified empirical likelihood approach for testing MCAR and subsequent estimation, Impact of imputation of missing values on classification error for discrete data, Inference functions and quadratic score tests, Can one assess whether missing data are missing at random in medical studies?, Mixtures of semiparametric varying coefficient models for longitudinal data with nonignorable dropout, Can one assess whether missing data are missing at random in medical studies?, Missing data mechanisms and homogeneity of means and variances-covariances, Unnamed Item, Identifying variables responsible for data not missing at random, Handling attrition in longitudinal studies: the case for refreshment samples