A logistic regression analysis approach for sample survey data based on phi-divergence measures
Methodology
2016-11-09 v1
Abstract
A new family of minimum distance estimators for binary logistic regression models based on -divergence measures is introduced. The so called "pseudo minimum phi-divergence estimator"(PME) family is presented as an extension of "minimum phi-divergence estimator" (ME) for general sample survey designs and contains, as a particular case, the pseudo maximum likelihood estimator (PMLE) considered in Roberts et al. \cite{r}. Through a simulation study it is shown that some PMEs have a better behaviour, in terms of efficiency, than the PMLE.
Cite
@article{arxiv.1611.02583,
title = {A logistic regression analysis approach for sample survey data based on phi-divergence measures},
author = {Elena Castilla and Nirian Martin and Leandro Pardo},
journal= {arXiv preprint arXiv:1611.02583},
year = {2016}
}