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Interpreting the Parameters of Log-Linear Models

Bibliographic Data

ID2331599
AuthorsR Alba (0000-0003-2966-441X, Albany State University, corresponding author), Richard D Alba (State University of New York at Albany)
Year1987
Volume16
Issue1
Pages45-77
Publication date1987-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociological Methods & Research (JOURNAL)
Journal identifiersISSN: 0049-1241 • E-ISSN: 1552-8294
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0049124187016001003
OpenAlexW2077419041
LanguageEN
Citations received30
References cited10

This article develops a straightforward approach to the interpretation of the parameters in log-linear models through a detailed consideration of examples. The focus is on models involving dependent variables, and the conventions of regression analysis are used to represent variables in models for the logit, or logarithm of the odds of the dependent variable. By simple manipulations, the parameters in logit models are related to such quantities as odds and odds ratios. The magnitudes of the effects conveyed by the parameters are also described in terms of typical percentage differences. The examples considered include models with complex interaction structures and for polytomous dependent variables. The mechanics of developing parameter estimates from the output of widely available computer programs are shown

Econometrics · Focus (optics) · Interpretation (philosophy) · Item response theory · Linear model · Linear regression · Log-linear model · Logarithm · Logistic regression · Logit · Mathematical analysis · Odds · Ordered logit · Polytomous Rasch model · Psychometrics · Statistics · Variable (mathematics) · Variables · Advanced Statistical Methods and Models · Computer Science · Mathematics · Statistical Methods and Applications · Water Quality and Resources Studies

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Unique citing works30
Citations per year0,79
Citation span1988 - 2022 (35)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 26

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