Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part I: Historical and Methodological Overview

DOI10.2307/1402613zbMath0478.62003OpenAlexW2324391196MaRDI QIDQ3936003

Gary G. Koch, Peter B. Imrey, Maura E. Stokes

Publication date: 1981

Published in: International Statistical Review / Revue Internationale de Statistique (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/1402613

zbMATH Keywords

surveymaximum likelihoodweighted least squaresiterative proportional fittingrakingfunctional asymptotic regression methodologyproduct-multinomial contingency table model

Mathematics Subject Classification ID

Contingency tables (62H17)

Related Items

AN INVESTIGATION OF GENERALIZED RAKINGIN THE SYNTHETIC ESTIMATION OFPOPULATION SIZE ⋮ Loglinear multidimensional IRT models for polytomously scored items ⋮ Log-linear models for mutations in the HIV genome ⋮ Comparing diagnostic tests with missing data ⋮ On the index of dissimilarity for lack of fit in loglinear and log-multiplicative models ⋮ A product-multinomial framework for categorical data analysis with missing responses ⋮ Nonparametric bayesian inference for dichotomous response models ⋮ The least squares estimation of the transition probabilities of binary processes on the basis of sample paths ⋮ Maximum likelihood methods for linear and log-linear models in categorical data ⋮ On a separation theorem for generalized eigenvalues and a problem in the analysis of sample surveys