Empirical distributions of parameter estimates in binary logistic regression using bootstrap

Citation

Fitrianto, Anwar and Ng, Mei Cing (2014) Empirical distributions of parameter estimates in binary logistic regression using bootstrap. International Journal of Mathematical Analysis, 8 (15). pp. 721-726. ISSN 1312-8876; ESSN: 1314-7579

Abstract

Bootstrapping is a famous statistical tool that involves resampling procedure to select sample from a population. In this study, we applied random-x bootstrap in binary logistic regression for published data set namely Umaru Impact data. We conducted bootstrap for the coefficient by using SAS (Statistical Analysis System). We observe the distribution of the estimated coefficients with different sample sizes. After conducting B=10000 bootstrap replications, we found that the distribution of parameters estimates is nearly normal.

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Science Institute for Mathematical Research
DOI Number:	https://doi.org/10.12988/ijma.2014.4394
Publisher:	Hikari
Keywords:	Binary logistic; Bootstrap; Parameter estimates
Depositing User:	Nabilah Mustapa
Date Deposited:	15 Sep 2015 10:10
Last Modified:	15 Sep 2015 10:10
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.12988/ijma.2014.4394
URI:	http://psasir.upm.edu.my/id/eprint/37433
Statistic Details:	View Download Statistic

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