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Log Linear Models for Contingency Tables: A Generalization of Classical Least Squares
Author(s) -
Nelder J. A.
Publication year - 1974
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2347125
Subject(s) - contingency table , generalization , mathematics , statistics , least squares function approximation , log linear model , econometrics , linear model , mathematical analysis , estimator
Summary Log linear models for contingency tables of counts are formulated as a special case of generalized linear models with an additive systematic component Y , Poisson errors for the data and an exponential linking function connecting the expected values of the observations with the predicted Y. Dichotomous response variates can be treated by an extension of this model or equivalently as another generalized linear model with binomial errors. A program package is described for fitting these models, and some redundancies in the literature noted.