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Semiparametric Regression Analysis of Survival and Longitudinal Data

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dc.contributor.advisor Diao, Guoqing Yuan, Mengdie
dc.creator Yuan, Mengdie en_US 2014-09-18T01:56:57Z 2014-09-18T01:56:57Z 2014-05 en_US
dc.description.abstract The proportional odds model is used in survival analysis when the odds ratios over time are constant. The assumption, however, is often violated in many applications. We propose a novel semiparametric general odds ratio model for the analysis of right-censored survival data. The proposed model incorporates the short-term and long-term covariate effects on the failure time data, and includes the proportional odds model as a special case. We derive efficient likelihood-based inference procedures and establish the large sample properties of the proposed nonparametric maximum likelihood estimators. Extensive simulation studies demonstrate the proposed methods perform well in practical settings. An application to a breast cancer study is provided.
dc.format.extent 130 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2014 Mengdie Yuan en_US
dc.subject Biostatistics en_US
dc.subject B-spline en_US
dc.subject generalized linear models en_US
dc.subject nonparametric likelihood en_US
dc.subject odds rate model en_US
dc.subject semiparametric modeling en_US
dc.subject sieve maximum likelihood estimators en_US
dc.title Semiparametric Regression Analysis of Survival and Longitudinal Data en_US
dc.type Dissertation en Doctoral en Statistical Science en George Mason University en

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