Pseudo minimum phi-divergence estimator for multinomial logistic regression with complex sample design
Methodology
2016-06-06 v1
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.
Cite
@article{arxiv.1606.01009,
title = {Pseudo minimum phi-divergence estimator for multinomial logistic regression with complex sample design},
author = {Elena Castilla and Nirian Martin and Leandro Pardo},
journal= {arXiv preprint arXiv:1606.01009},
year = {2016}
}