Aggregation of Explanatory Factor Levels in a Binomial Logit Model: Generalization to the Multifactorial Unsaturated Case

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Autor principal: Ernesto Ponsot-Balaguer
Formato: Artículo científico
Lenguaje:en
Publicado: Universidad Nacional de Colombia 2012
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author Ernesto Ponsot-Balaguer
author_facet Ernesto Ponsot-Balaguer
contents Aggregation of Explanatory Factor Levels in a Binomial Logit Model: Generalization to the Multifactorial Unsaturated Case Ernesto Ponsot-Balaguer Surendra Sinha Arnaldo Goitía Física, Astronomía y Matemáticas Levels sets Logit model Contingency tables Generalized linear model We discuss a situation in which, once a logit model is fitted to the data in a contingency table, some factor levels are grouped. Generally, researchers reapply a logit model on the pooled data, however, this approach leads to the violation of the original distributional assumption, when the probabilities of success of the random variables of aggregation differ. In this paper we suggest an alternative procedure that operates under the unsaturated, multifactorial, binomial, logit model. Based on asymptotic theory and taking advantage of the decrease in the variance when the correct distributional assumption is made, the suggested procedure signi¿cantly improves the estimates, reduces the standard error, produces lower residuals and is less likely to reject the goodness of ¿t test on the model. We present the necessary theory, the results of an extensive simulation designed for this purpose, and the suggested procedure contrasted with the usual approach, through a complete numerical example. 2012 artículo científico 0120-1751 https://www.redalyc.org/articulo.oa?id=89923145010 en http://www.redalyc.org/revista.oa?id=899 Revista Colombiana de Estadística application/pdf Universidad Nacional de Colombia Revista Colombiana de Estadística (Colombia) Num.1 Vol.35
format Artículo científico
id redalyc_89923145010
institution Redalyc
language en
publishDate 2012
publisher Universidad Nacional de Colombia
spellingShingle Aggregation of Explanatory Factor Levels in a Binomial Logit Model: Generalization to the Multifactorial Unsaturated Case
Ernesto Ponsot-Balaguer
Física, Astronomía y Matemáticas
Levels sets
Logit model
Contingency tables
Generalized linear model
Aggregation of Explanatory Factor Levels in a Binomial Logit Model: Generalization to the Multifactorial Unsaturated Case Ernesto Ponsot-Balaguer Surendra Sinha Arnaldo Goitía Física, Astronomía y Matemáticas Levels sets Logit model Contingency tables Generalized linear model We discuss a situation in which, once a logit model is fitted to the data in a contingency table, some factor levels are grouped. Generally, researchers reapply a logit model on the pooled data, however, this approach leads to the violation of the original distributional assumption, when the probabilities of success of the random variables of aggregation differ. In this paper we suggest an alternative procedure that operates under the unsaturated, multifactorial, binomial, logit model. Based on asymptotic theory and taking advantage of the decrease in the variance when the correct distributional assumption is made, the suggested procedure signi¿cantly improves the estimates, reduces the standard error, produces lower residuals and is less likely to reject the goodness of ¿t test on the model. We present the necessary theory, the results of an extensive simulation designed for this purpose, and the suggested procedure contrasted with the usual approach, through a complete numerical example. 2012 artículo científico 0120-1751 https://www.redalyc.org/articulo.oa?id=89923145010 en http://www.redalyc.org/revista.oa?id=899 Revista Colombiana de Estadística application/pdf Universidad Nacional de Colombia Revista Colombiana de Estadística (Colombia) Num.1 Vol.35
title Aggregation of Explanatory Factor Levels in a Binomial Logit Model: Generalization to the Multifactorial Unsaturated Case
topic Física, Astronomía y Matemáticas
Levels sets
Logit model
Contingency tables
Generalized linear model
url https://www.redalyc.org/articulo.oa?id=89923145010