Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data

Hayriye Esra AKYUZ; Hamza GAMGAM

Makale detayları

Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data

Yazarlar:

Hayriye Esra AKYUZ | Hamza GAMGAM

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2019 Vol.32 Issue 1, pp.318-331

Belge Tipi:

Makale

Yayın Tarihi:

2/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000428089

eISSN:

2147-1762

Özet:

 


This study is aimed to obtain
an appropriate logistic regression model based on the bootstrap methods. For
this purpose, two bootstrap methods called bootstrap I and bootstrap II are
given to obtain the estimations of parameters and standard errors. Traditional
logistic regression is compared with the bootstrap I and bootstrap II methods
in terms of the parameter estimations and standard errors. It has been found
that the standard errors of the parameter estimations for the bootstrap I model
are smaller than others. Also, the average widths of confidence interval based
on bootstrap I model are narrower than the logistic regression and bootstrap
II. It is seen that, the simulation study based on different sample sizes
supports these results. It can be said that the bootstrap I model based on
resampling of errors term is the best in estimating coronary artery disease.


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Makale detayları

Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data

Yazarlar: Hayriye Esra AKYUZ | Hamza GAMGAM

Yayıncı: Gazi University

Ana Başlıklar: Uygulamalı fizik

Dergi: Gazi University Journal of Science 2019 Vol.32 Issue 1, pp.318-331

Belge Tipi: Makale

Yayın Tarihi: 2/2019

Belge Dili: İngilizce

Document ID (Org No.): 2000428089

eISSN: 2147-1762

Sayı

Yazarlar:

Hayriye Esra AKYUZ | Hamza GAMGAM

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2019 Vol.32 Issue 1, pp.318-331

Belge Tipi:

Makale

Yayın Tarihi:

2/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000428089

eISSN:

2147-1762