In observational studies researchers often have access to multiple sources of information but ultimately choose to apply well-established statistical methods that do not take advantage of the full range of information ...

One major aim of statistics is to systematically study outcomes of interest in a population by observing the properties of a sample of that population. Some outcomes, such as the total number of people infected in an ...

Stratified medicine has tremendous potential to deliver more effective therapeutic intervention to improve public health. For practical implementation, reliable prediction models and clinically meaningful categorization ...

In chapter one a Liability Threshold Mixed Linear Model (LTMLM) association statistic is introduced for ascertained case-control studies that increases power vs. existing mixed model methods for diseases with low prevalence, ...

In this dissertation, we propose methodology to account for missing data as well as a strategy to account for outcome heterogeneity. Missing data occurs frequently in empirical studies in health and social sciences, often ...

In chapter 1, we consider the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and sensitivity analysis techniques to correct for such biases. We give an analysis of ...

Case-control genetic sequencing studies are increasingly being conducted to identify rare variants associated with complex diseases. Oftentimes, these studies collect a variety of secondary traits--quantitative and qualitative ...

In the present dissertation we consider three classical problems in biostatistics and statistical learning - classification, variable selection and statistical inference. Chapter 2 is dedicated to multi-class classification. ...