A Constructive Procedure for Modeling Categorical Variables: Log-Linear and Logit Models
| Autor: | Cheng, Philip E., Liou, Jiun-Wei, Kao, Hung-Wen, Liou, Michelle |
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| Rok vydání: | 2018 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | 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. Comment: This article sets up a new construction methodology for selecting the most parsimonious log-linear and logit models in any finite-dimensional categorical data table using the analysis of information identity. Please refer this article to arXiv: 1801.01003 [stat.ME] and Cheng et al. (JASA, 2010). Email your comments and questions to the corresponding author |
| Databáze: | arXiv |
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