Log-linear models

Edited book (chapter)

Dunn, Peter K.. 2004. "Log-linear models." Kempf-Leonard, Kimberley (ed.) Encyclopedia of social measurement. Dallas, TX. USA. Elsevier. pp. 585-589
Chapter Title

Log-linear models

Book Chapter CategoryEdited book (chapter)
ERA Publisher ID1821
Book TitleEncyclopedia of social measurement
Authors
AuthorDunn, Peter K.
EditorsKempf-Leonard, Kimberley
Volume2
Page Range585-589
Number of Pages5
Year2004
PublisherElsevier
Place of PublicationDallas, TX. USA
ISBN0124438903
Abstract

A large amount of data collected in the social sciences are counts crossclassified into categories. These counts are non-negative integers and require
special methods of analysis to model appropriately; log-linear models are one
sophisticated method. The counts are modeled by the Poisson distribution,
and related to the classifying variables through a logarithm. Models can then
be built, critically analysed, evaluated and compared to develop a suitable
statistical model for modeling the count data. Log-linear models are powerful
enough to cope with many classifying variables, and permit many model
building ideas similar to those in standard statistical regression.

Keywordscontingency table, factor, level, poisson distribution, treatment coding, log-linear models
ANZSRC Field of Research 2020490509. Statistical theory
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Byline AffiliationsDepartment of Mathematics and Computing
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