Statistical Models Commons^™

Statistical Methods For Two Problems In Cancer Research: Analysis Of Rna-Seq Data From Archival Samples And Characterization Of Onset Of Multiple Primary Cancers, Jialu Li

Dissertations & Theses (Open Access)

My dissertation is focused on quantitative methodology development and application for two important topics in translational and clinical cancer research.

The first topic was motivated by the challenge of applying transcriptome sequencing (RNA-seq) to formalin-fixation and paraffin-embedding (FFPE) tumor samples for reliable diagnostic development. We designed a biospecimen study to directly compare gene expression results from different protocols to prepare libraries for RNA-seq from human breast cancer tissues, with randomization to fresh-frozen (FF) or FFPE conditions. To comprehensively evaluate the FFPE RNA-seq data quality for expression profiling, we developed multiple computational methods for assessment, such as the uniformity and continuity …

Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane

Theses

Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …

Further Advances For The Sequential Multiple Assignment Randomized Trial (Smart), Tianjiao Dai

Dissertations & Theses (Open Access)

ABSTRACT

FURTHER ADVANCES FOR THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL (SMART)

Tianjiao Dai, M.S.

Advisory Professor: Sanjay Shete, Ph.D.

Sequential multiple assignment randomized trial (SMART) designs have been developed these years for studying adaptive interventions. In my Ph.D. study, I mainly investigate how to further improve SMART designs and optimize the interventions for each individual in the trial. My dissertation has focused on two topics of SMART designs.

1) Developing a novel SMART design that can reduce the cost and side effects associated with the interventions and proposing the corresponding analytic methods. I have developed a time-varying SMART design in …

An Exploratory Statistical Method For Finding Interactions In A Large Dataset With An Application Toward Periodontal Diseases, Joshua Lambert

Theses and Dissertations--Epidemiology and Biostatistics

It is estimated that Periodontal Diseases effects up to 90% of the adult population. Given the complexity of the host environment, many factors contribute to expression of the disease. Age, Gender, Socioeconomic Status, Smoking Status, and Race/Ethnicity are all known risk factors, as well as a handful of known comorbidities. Certain vitamins and minerals have been shown to be protective for the disease, while some toxins and chemicals have been associated with an increased prevalence. The role of toxins, chemicals, vitamins, and minerals in relation to disease is believed to be complex and potentially modified by known risk factors. A …