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Association Models for Clustered Data with Binary and Continuous Responses

This dissertation develops novel single random effect models as well as bivariate correlated random effects model for clustered data with bivariate mixed responses. Logit and identity link functions are used for the binary and continuous responses. For the ease of interpretation of the regression effects, random effect of the binary response has bridge distribution so that the marginal model of mean of the binary response after integrating out the random effect preserves logistic form. And the marginal regression function of the continuous response preserves linear form. Within-cluster and within-subject associations could be measured by our proposed models. For the bivariate correlated random effects model, we illustrate how different levels of the association between two random effects induce different Kendall's tau values for association between the binary and continuous responses from the same cluster. Fully parametric and semi-parametric Bayesian methods as well as maximum likelihood method are illustrated for model analysis. In the semiparametric Bayesian model, normality assumption of the regression error for the continuous response is relaxed by using a nonparametric Dirichlet Process prior. Robustness of the bivariate correlated random effects model using ML method to misspecifications of regression function as well as random effect distribution is investigated by simulation studies. The Bayesian and likelihood methods are applied to a developmental toxicity study of ethylene glycol in mice. / A Dissertation Submitted to the Department of Statistics in Partial FulīŦLlment of
the Requirements for the Degree of Doctor of Philosophy. / Spring Semester, 2009. / April 8, 2009. / Dirichlet Process Prior, Bivariate Binary And Continuous Responses, Copula Model, Bridge Distribution, Bayesian Analysis, MCMC / Includes bibliographical references. / Debajyoti Sinha, Professor Directing Dissertation; Myra Hurt, Outside Committee Member; Stuart R. Lipsitz, Committee Member; Daniel McGee, Committee Member.
ContributorsLin, Lanjia, 1981- (authoraut), Sinha, Debajyoti (professor directing dissertation), Hurt, Myra (outside committee member), Lipsitz, Stuart R. (committee member), McGee, Daniel (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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