Suay EreesAylin Alin2025-10-06201715324141, 036109180361-09181532-414110.1080/03610918.2015.1016238https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995542972&doi=10.1080%2F03610918.2015.1016238&partnerID=40&md5=be7135db6e96dc23a30a0bc007b361f6https://gcris.yasar.edu.tr/handle/123456789/9692Violation of correct specification may cause some undesirable results such as biased logistic regression coefficients and less efficient test statistics. In this paper asymptotic relative efficiency (ARE) of various coefficients of determination in misspecified binary logistic regression models is investigated. Seven types of misspecification have been included. ARE of test statistics for exponential and Weibull distributions as a method of calculating optimal cutpoints is derived to demonstrate misspecification. Theoretical relationships between coefficients of determination have also been analyzed. Extensive simulations using bootstrap method and a real data application reveal more efficient one under various modeling scenarios. © 2017 Elsevier B.V. All rights reserved.EnglishAsymptotic Relative Efficiency, Coefficients Of Determination, Land Consolidation, Misspecification, Regression Analysis, Statistical Tests, Statistics, Weibull Distribution, Asymptotic Relative Efficiency, Binary Logistic Regression Models, Bootstrap Method, Coefficients Of Determination, Extensive Simulations, Land Consolidations, Logistic Regressions, Misspecification, EfficiencyRegression analysis, Statistical tests, Statistics, Weibull distribution, Asymptotic relative efficiency, Binary logistic regression models, Bootstrap method, Coefficients of determination, Extensive simulations, Land consolidations, Logistic regressions, Misspecification, EfficiencyArticle