This dissertation focuses on two topics in semiparametric statistical methods and their applications in medical science: (1) prediction of patients? lifetimes based on their risk profiles; (2) estimation of dynamic exposure effects on survival outcomes. In Chapter II, we develop multiple...

Spatial or spatio-temporal data are frequently encountered in many scientific disciplines. One major challenge in modeling these processes is the high dimensionality of such data; that is, the number of observations is usually enormous. The first part of the dissertation proposes an efficient...

Purpose In promotional ads that contain both the Regular Price and Sale Price information, this paper aims to investigate whether changing the font sizes of these two prices has an effect on how consumers process the ad message. The authors use acquisition-transaction utility perspective to...

In much of applied statistics variables of interest are measured with error. In particular, regression with covariates that are subject to measurement error requires adjustment to avoid biased estimates and invalid inference. We consider two aspects of this problem. Detection Limits (DL) arise...

This thesis develops methodology and asymptotic analysis for sparse estimators of the covariance matrix and the inverse covariance (concentration) matrix in high-dimensional settings. We propose estimators that are invariant to the ordering of the variables and estimators that exploit variable...

Cluster randomized trials, in which social units are selected as the units ofrandomization, have been increasingly used in the past three decades to evaluatethe effects of intervention. This thesis is devoted to design and analysis of clusterrandomized trials.Regarding design, we introduce a new...