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Goodness-of-Tests for Logistic Regression

The generalized linear model and particularly the logistic model are widely used in public health, medicine, and epidemiology. Goodness-of-fit tests for these models are popularly used to describe how well a proposed model fits a set of observations. These different goodness-of-fit tests all have individual advantages and disadvantages. In this thesis, we mainly consider the performance of the "Hosmer-Lemeshow" test, the Pearson's chi-square test, the unweighted sum of squares test and the cumulative residual test. We compare their performance in a series of empirical studies as well as particular simulation scenarios. We conclude that the unweighted sum of squares test and the cumulative sums of residuals test give better overall performance than the other two. We also conclude that the commonly suggested practice of assuming that a p-value less than 0.15 is an indication of lack of fit at the initial steps of model diagnostics should be adopted. Additionally, D'Agostino et al. presented the relationship of the stacked logistic regression and the Cox regression model in the Framingham Heart Study. So in our future study, we will examine the possibility and feasibility of the adaption these goodness-of-fit tests to the Cox proportional hazards model using the stacked logistic regression. / A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of
Doctor of Philosophy. / Fall Semester, 2010. / August 19, 2010. / Generalized Linear Model, Stacked Logistic Regression, Goodness-of-fit Tests, Logistic Regression / Includes bibliographical references. / Dan L. McGee, Professor Co-Directing Dissertation; Jinfeng Zhang, Professor Co-Directing Dissertation; Myra Hurt, University Representative; Debajyoti Sinha, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_253874
ContributorsWu, Sutan, 1983- (authoraut), McGee, Dan L. (professor co-directing dissertation), Zhang, Jinfeng (professor co-directing dissertation), Hurt, Myra (university representative), Sinha, Debajyoti (committee member), Department of Statistics (degree granting department), Florida State University (degree granting institution)
PublisherFlorida State University, Florida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource, computer, application/pdf
RightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.

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