The first-order Markov conditional linear expectation approach for analysis of longitudinal Data

DOI10.1002/sim.8883zbMATH Open1546.62089MaRDI QIDQ6627737

Peter P. Reese, Daniel Lloyd Gray, Shaun Bender, Victoria Gamerman, Yimei Li, Justine Shults

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

discrete datageneralized estimating equationsbinary random variablesfirst-order antedependencefirst-order Markov

Mathematics Subject Classification ID

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

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Generalized estimating equations.
• A family of generalized linear models for repeated measures with normal and conjugate random effects
• Negative Binomial Regression
• Akaike's Information Criterion in Generalized Estimating Equations
• Some Covariance Models for Longitudinal Count Data with Overdispersion
• Correlated Binary Regression with Covariates Specific to Each Binary Observation
• The most-cited statistical papers
• The asymptotic properties of ML estimators when sampling from associated populations
• Ante-dependence Analysis of an Ordered Set of Variables
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Longitudinal and Panel Data
• Modeling longitudinal binomial responses: implications from two dueling paradigms
• Quasi-Least Squares Regression
• On the Distribution of the Likelihood Ratio
• A Note on the Simulation of Overdispersed Random Variables With Specified Marginal Means and Product Correlations

This page was built for publication: The first-order Markov conditional linear expectation approach for analysis of longitudinal Data