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*_Notice and Invitation_* Oral Defense of Doctoral Dissertation Department of Statistics Volgenau School of Engineering, George Mason University *Mengdie Yuan* Bachelor of Science, Statistics, University of Science and Technology of China, 2009* *Master of Science, Statistical Science, George Mason University, 2011* * *Semiparametric Regression Analysis of Survival and Longitudinal Data* Monday, April 28^th , 2014 10:30 AM to 12:30 PM The Nguyen Engineering Building, Room 3507 All are invited to attend. *_Committee_* Guoqing Diao, Chair Jacqueline Hughes-Oliver Anand Vidyashankar Ali Weinstein *_Abstract_* The proportional odds model is a popular model in survival analysis. The assumption of constant odds ratios over time in the proportional odds model, 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. Secondly, we study the generalized linear models with an unknown link function for both data with independent observations and longitudinal data. We propose sieve maximum likelihood estimation procedures for both fixed effects models and random effects models by using B-splines. We establish the consistency and asymptotic normality of the proposed sieve maximum likelihood estimators.Extensive simulation studies along with an application to anepileptic study are provided to evaluate the finite-sample performance of the proposed methods. A copy of this doctoral dissertation will be on reserve at the Johnson Center Library.