Volume 2, Issue 3, September 2017, Page: 107-110
Bootstrapping Pseudo - R2 Measures for Binary Response Variable Model
Zakariya Yahya Algamal, Department of Statistics and Informatics, University of Mosul, Mosul, Iraq
Haithem Taha Mohammad Ali, College of Computers and Information Technology, Nawroz University, Kurdistan Region, Iraq
Received: Mar. 7, 2017;       Accepted: Mar. 16, 2017;       Published: Mar. 31, 2017
DOI: 10.11648/j.bsi.20170203.13      View  1421      Downloads  107
Abstract
Statistical inference is based generally on some estimates that are functions of the data. Bootstrapping procedure offers strategies to estimate or approximate the sampling distribution of a statistic. Logistics regression model with binary response is commonly used. This paper focuses on the behavior of bootstrapping pseudo - R2 measures in logistic regression model. Simulation and real data results also presented. We conclude and suggest to use either R2M or R2D, since they have convergence in there values.
Keywords
Logistic Regression, Pseudo - R2, Bootstrap, Logit, Propit
To cite this article
Zakariya Yahya Algamal, Haithem Taha Mohammad Ali, Bootstrapping Pseudo - R2 Measures for Binary Response Variable Model, Biomedical Statistics and Informatics. Vol. 2, No. 3, 2017, pp. 107-110. doi: 10.11648/j.bsi.20170203.13
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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