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  1651      Downloads  120
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.
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
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