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arXiv · 1606.01009

Pseudo minimum phi-divergence estimator for multinomial logistic regression with complex sample design

Elena Castilla·Nirian Martin·Leandro Pardo
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Abstract

This article develops the theoretical framework needed to study the multinomial logistic regression model for complex sample design with pseudo minimum phi-divergence estimators. Through a numerical example and simulation study new estimators are proposed for the parameter of the logistic regression model with overdispersed multinomial distributions for the response variables, the pseudo minimum Cressie-Read divergence estimators, as well as new estimators for the intra-cluster correlation coefficient. The results show that the Binder's method for the intra-cluster correlation coefficient exhibits an excellent performance when the pseudo minimum Cressie-Read divergence estimator, with lambda = 2/3 , is plugged.

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Elena Castilla, Nirian Martin, Leandro Pardo. 2016-06-03. Pseudo minimum phi-divergence estimator for multinomial logistic regression with complex sample design. https://arxiv.org/abs/1606.01009

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