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Association Models for Clustered Data with Binary and Continuous Responses

Title: Association Models for Clustered Data with Binary and Continuous Responses.
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Name(s): Lin, Lanjia, 1981-, author
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
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2009
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: 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.
Identifier: FSU_migr_etd-1330 (IID)
Submitted Note: A Dissertation Submitted to the Department of Statistics in Partial FulfiLlment of the Requirements for the Degree of Doctor of Philosophy.
Degree Awarded: Spring Semester, 2009.
Date of Defense: April 8, 2009.
Keywords: Dirichlet Process Prior, Bivariate Binary And Continuous Responses, Copula Model, Bridge Distribution, Bayesian Analysis, MCMC
Bibliography Note: Includes bibliographical references.
Advisory committee: Debajyoti Sinha, Professor Directing Dissertation; Myra Hurt, Outside Committee Member; Stuart R. Lipsitz, Committee Member; Daniel McGee, Committee Member.
Subject(s): Statistics
Probabilities
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_migr_etd-1330
Owner Institution: FSU

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Lin, L. (2009). Association Models for Clustered Data with Binary and Continuous Responses. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-1330