Behaviormetrika
Online ISSN : 1349-6964
Print ISSN : 0385-7417
ISSN-L : 0385-7417
MAXIMUM LIKELIHOOD METHODS FOR ASSOCIATION MODELS IN ORDERED CATEGORICAL DATA: MULTI-WAY CASE
Masaaki Tsujitani
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1988 年 15 巻 23 号 p. 85-91

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Log-linear models have played a central role in analyzing the contingency tables. These models fail to exploit all the available information about the category orderings. Goodman (1979, 1981a, b) has recently proposed a general class of models for the analysis of association in cross-classifications having ordered categories. Clogg (1982), Agresti (1983) and Agresti & Kezouh (1983) extended his method to multi-way cross-classifications. This article presents the maximum likelihood methods to obtain parameter estimates for the analysis of association in multi-way case.

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© The Behaviormetric Society of Japan
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