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arXiv · 1801.01278

A Constructive Procedure for Modeling Categorical Variables: Log-Linear and Logit Models

Philip E. Cheng·Jiun-Wei Liou·Hung-Wen Kao·Michelle Liou
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Abstract

Association between categorical variables in contingency tables is analyzed using the information identities based on multivariate multinomial distributions. A scheme of geometric decompositions of the information identities is developed to identify indispensable predictors and interaction effects in the construction of concise log-linear and logit models; it suggests a new approach for selecting parsimonious log-linear and logit models which would facilitate the search for the minimum AIC models as a byproduct. The proposed constructive schemes are illustrated along with the analysis of a contingency data table collected in a study on the risk factors of ischemic cerebral stroke.

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Philip E. Cheng, Jiun-Wei Liou, Hung-Wen Kao, Michelle Liou. 2018-01-04. A Constructive Procedure for Modeling Categorical Variables: Log-Linear and Logit Models. https://arxiv.org/abs/1801.01278

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