Specifications of models for cross-classified counts:Comparison of the log-linear models and marginal models perspectives  

Oleh:

Becker, Mark P. ; Yang, Ilsoon ; Minick, Susan

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Sociological Methods & Research (SMR) vol. 26 no. 04 (May 1998), page 511-529.
Topik: sociological research; family

Ketersediaan

Perpustakaan PKPM Nomor Panggil: S28 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Log-linear models are useful for analyzjng cross-classifications of counts arising in sociology, but it has been argued that in some cases, an alternative approach for formulating models-one based on simultaneously modeling univariate marginal logits and marginal associations-{;an lead to models that are more directly relevant for addressing the kinds of questions arising in those cases. In this article, the authors explore some of the similarities and differences between the log-linear models approach to modeling categorical data and a marginal modeling approach. It has been noted in past literature that the model of statistical independence is conveniently represented within both approaches to specifying models for cross-classifications of counts. The authors examine further the extent to which the two families of models overlap, as well as some important differences. The authors do not present a complete characterization of the conditions describing the intersection of the two families of models but cover many of the models for bivariate contingency tables and for three-way contingency tables that are routinely used in sociological research.

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