Inference on treatment effect in a pretest–posttest study is a routine objective in medicine, public health, and other fields, and a number of approaches have been advocated. Typically, subjects are randomized to two treatments, the response is measured at baseline and a prespecified...

This article proposes a semiparametric two-step procedure for estimating a censored consumer demand system with micro data. The semiparametric estimator considered in the first step is suggested by Klein and Spady (1993). This estimator, used as a counterpart of the probit estimator in a...

In this dissertation, the generalized score tests based on weighted estimating equationsare proposed for missing covariate data. Their properties, including the effectsof nuisance functions on the forms of the test statistics and efficiency of the tests,are investigated. Different versions of...

We introduce a new method to robustifying inference that can be applied in any situation where a parametric likelihood is available. The key feature is that data from the postulated parametric models are assumed to be measured with error where the measurement error distribution is chosen to...

In the first part of the dissertation, we derive two methods for responders analysis in longitudinal data with random missing data. Often a binary variable is generated by dichotomizing an underlying continuous variable measured at a specific point in time according to a prespecified threshold...

This thesis addresses three major issues in data mining regarding feature subset selection in large dimensionality domains, plausible reconstruction of incomplete data in cross-sectional applications, and forecasting univariate time series. For the automated selection of an optimal subset of...

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 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...

This thesis is comprised of three chapters. The first chapter develops a statistical model that enriches the role that firms playin wage determination, allowing firms to influence both average wages as well as the returns to observable worker characteristics. I exploit the hierarchical nature of...

It is of interest that researchers study competing risks in which subjects may fail from any one of K causes. Comparing any two competing risks with covariate effects is very important in medical studies. This thesis develops omnibus tests for comparing cause-specific hazard rates and cumulative...