Log-linear models

Dunn, Peter K. (2004) Log-linear models. In: Encyclopedia of social measurement. Elsevier, Dallas, TX. USA, pp. 585-589. ISBN 0124438903

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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.


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Item Type: Book Chapter (Commonwealth Reporting Category B)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to paper due to publishers copyright restrictions. Print copy held in USQ Library at call no. 300.72 Enc.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 11 Oct 2007 00:20
Last Modified: 02 Jul 2013 22:32
Uncontrolled Keywords: contingency table, factor, level, poisson distribution, treatment coding, log-linear models
Fields of Research (FOR2008): 01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory
URI: http://eprints.usq.edu.au/id/eprint/380

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