Empirical distributions of parameter estimates in binary logistic regression using bootstrap

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 (Stati...

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Main Authors: Fitrianto, Anwar, Ng, Mei Cing
Format: Article
Language:English
Published: Hikari 2014
Online Access:http://psasir.upm.edu.my/id/eprint/37433/
http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf
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author Fitrianto, Anwar
Ng, Mei Cing
author_facet Fitrianto, Anwar
Ng, Mei Cing
author_sort Fitrianto, Anwar
building UPM Institutional Repository
collection Online Access
description 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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institution Universiti Putra Malaysia
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spelling upm-374332015-09-15T10:10:23Z http://psasir.upm.edu.my/id/eprint/37433/ Empirical distributions of parameter estimates in binary logistic regression using bootstrap Fitrianto, Anwar Ng, Mei Cing 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. Hikari 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf 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 http://www.m-hikari.com/ijma/ijma-2014/ijma-13-16-2014/fitriantoIJMA13-16-2014-2.pdf 10.12988/ijma.2014.4394
spellingShingle Fitrianto, Anwar
Ng, Mei Cing
Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_full Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_fullStr Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_full_unstemmed Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_short Empirical distributions of parameter estimates in binary logistic regression using bootstrap
title_sort empirical distributions of parameter estimates in binary logistic regression using bootstrap
url http://psasir.upm.edu.my/id/eprint/37433/
http://psasir.upm.edu.my/id/eprint/37433/
http://psasir.upm.edu.my/id/eprint/37433/
http://psasir.upm.edu.my/id/eprint/37433/1/Empirical%20Distributions%20of%20Parameter%20Estimates.pdf