Model diagnostics for marginal regression analysis of correlated binary data

DOI10.1080/03610919708813396zbMath0900.62392OpenAlexW2035489103MaRDI QIDQ4369360

Michael H. Kutner, Yinsheng Qu, Ming Tan

Publication date: 18 December 1997

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610919708813396

zbMATH Keywords

GEEmodel adequacy checkingcorrelated logistic regression

Mathematics Subject Classification ID

Diagnostics, and linear inference and regression (62J20)

Related Items (12)

A new approach to modeling positive random variables with repeated measures ⋮ REGRESSION DIAGNOSTIC USING LOCAL INFLUENCE: A REVIEW ⋮ Influence measures based on the volume of confidence ellipsoids for GEE ⋮ Outlier detection method in GEEs ⋮ Properties of prior and posterior distributions for multivariate categorical response data models ⋮ Verification of the mathematical model of a multidimensional dynamic system for adequacy based on the spectral norm of a residual matrix ⋮ Hierarchical models for repeated binary data using the IBF sampler ⋮ Bayesian analysis of correlated mixed categorical data by incorporating historical prior information ⋮ Robustness of the Latent Variable Model for Correlated Binary Data ⋮ Marginal Models for Longitudinal Continuous Proportional Data ⋮ Diagnostic techniques in generalized estimating equations ⋮ Generalized additive partial linear models for analyzing correlated data

Cites Work

• Unnamed Item
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• Longitudinal data analysis using generalized linear models
• Logistic regression diagnostics
• Correlated Binary Regression with Covariates Specific to Each Binary Observation
• The Maximum Likelihood Estimation of Correlation from Contingency Tables
• Graphical Methods for Assessing Logistic Regression Models
• Goodness of fit tests for the multiple logistic regression model
• Two graphical displays for outlying and influential observations in regression
• Regression Model Diagnostics
• Exploring Partial Residual Plots
• Latent Variable Models for Clustered Ordinal Data

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