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New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models

The binary (or binomial) logistic regression model (LRM) is one of the generalised linear models (GLMs). It is used when the dependent variable is dichotomous and the independent variables are of any type. LRM are popular in many applications and in different disciplines including biomedical and...

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Main Author: Hussain, Jassim Nassir
Format: Thesis
Language:English
Published: 2013
Subjects:
QA1 Mathematics (General)
Online Access:http://eprints.usm.my/43278/1/Jassim%20Nassir%20Hussain24.pdf
http://eprints.usm.my/43278/
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spelling my.usm.eprints.43278 http://eprints.usm.my/43278/ New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models Hussain, Jassim Nassir QA1 Mathematics (General) The binary (or binomial) logistic regression model (LRM) is one of the generalised linear models (GLMs). It is used when the dependent variable is dichotomous and the independent variables are of any type. LRM are popular in many applications and in different disciplines including biomedical and social sciences. Assessing the goodness-of-fit (GOF) is considered to be the important step after fitting the model to show the adequacy of the LRM in fitting the observations. The GOF test is defined as an evaluation of how well the estimated outcomes agree with the observed data. Two techniques may be used to construct the GOF test statistics of chi-square type. The first technique is based on ungrouped observations. This technique is not preferred in the LRM for many reasons including that the obtained distribution and 2013-04 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/43278/1/Jassim%20Nassir%20Hussain24.pdf Hussain, Jassim Nassir (2013) New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA1 Mathematics (General)
spellingShingle QA1 Mathematics (General)
Hussain, Jassim Nassir
New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
description The binary (or binomial) logistic regression model (LRM) is one of the generalised linear models (GLMs). It is used when the dependent variable is dichotomous and the independent variables are of any type. LRM are popular in many applications and in different disciplines including biomedical and social sciences. Assessing the goodness-of-fit (GOF) is considered to be the important step after fitting the model to show the adequacy of the LRM in fitting the observations. The GOF test is defined as an evaluation of how well the estimated outcomes agree with the observed data. Two techniques may be used to construct the GOF test statistics of chi-square type. The first technique is based on ungrouped observations. This technique is not preferred in the LRM for many reasons including that the obtained distribution and
format Thesis
author Hussain, Jassim Nassir
author_facet Hussain, Jassim Nassir
author_sort Hussain, Jassim Nassir
title New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
title_short New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
title_full New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
title_fullStr New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
title_full_unstemmed New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
title_sort new test statistics to assess the goodness-of-fit of logistic regression models
publishDate 2013
url http://eprints.usm.my/43278/1/Jassim%20Nassir%20Hussain24.pdf
http://eprints.usm.my/43278/
_version_ 1643710706831327232
score 13.18916

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