A comparative study on the performance of frequentist and Bayesian estimation methods under separation in logistic regression
Yazarlar (1)
Doç. Dr. Yasin ALTINIŞIK Sinop Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (ESCI dergilerinde yayınlanan tam makale)
Dergi Adı Communications Faculty of Sciences University of Ankara Series A1: Mathematics and Statistics
Dergi ISSN 1303-5991 Dergi Bilgileri (2020)
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili İngilizce Basım Tarihi 12-2020
Kabul Tarihi – Yayınlanma Tarihi 06-07-2020
Cilt / Sayı / Sayfa 69 / 2 / 1083–1103 DOI 10.31801/cfsuasmas.614492
Makale Linki https://dergipark.org.tr/en/download/article-file/1190031
UAK Araştırma Alanları
İstatistiksel Analiz Uygulamalı İstatistik Teorik İstatistik
Özet
Separation is one of the most commonly encountered estimation
problems in the context of logistic regression, which often occurs with small and medium sample sizes. The method of maximum likelihood (MLE) provides spuriously high parameter estimates and their standard errors under separation in logistic regression. Many researchers in social science...
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