A logistic regression analysis approach for sample survey data based on phi-divergence measures

2016/11/08 by Elena Castilla, Castilla, Elena, Nirian Martín +4
Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Methodology (stat.ME) #stat.ME

paper · pdf · doi:10.48550/arxiv.1611.02583

arxiv created 2016/11/08 · openalex publication_date 2016/11/08 · arxiv updated 2016/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A new family of minimum distance estimators for binary logistic regression models based on ϕ-divergence measures is introduced. The so called "pseudo minimum phi-divergence estimator"(PMϕE) family is presented as an extension of "minimum phi-divergence estimator" (MϕE) for general sample survey designs and contains, as a particular case, the pseudo maximum likelihood estimator (PMLE) considered in Roberts et al. \citer. Through a simulation study it is shown that some PMϕEs have a better behaviour, in terms of efficiency, than the PMLE.

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