Biostatistics Commons^™

Doubly Robust Estimates For Binary Longitudinal Data Analysis With Missing Response And Missing Covariates, Baojiang Chen, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Longitudinal studies often feature incomplete response and covariate data. Likelihood-based methods such as the EM algorithm give consistent estimators for model parameters when data are missing at random provided that the response model and the missing covariate model are correctly specified; but we do not need to specify the missing data mechanism. An alternative method is the weighted estimating equation which gives consistent estimators if the missing data and response models are correctly specified; but we do not need to specify the distribution of the covariates that have missing values. In this paper we develop a doubly robust estimation method …

Semiparametric Estimation Of The Covariate-Specific Roc Curve In Presence Of Ignorable Verification Bias, Danping Liu, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Covariate-specific ROC curves are often used to evaluate the classification accuracy of a medical diagnostic test or a biomarker, when the accuracy of the test is associated with certain covariates. In many large-scale screening tests, the gold standard is subject to missingness due to high cost or harmfulness to the patient. In this paper, we propose a semiparametric estimation method for the covariate-specific ROC curves with a partial missing gold standard. A location-scale model is constructed for the test result to model the covariates' effect, but the residual distributions are left unspecified. Thus the baseline and link functions of the …

Evaluating Markers For Treatment Selection Based On Survival Time, Xiao Song, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

For many medical conditions there are several treatment options available to patients. We consider evaluating markers based on a simple treatment selection policy that incorporates information on the patient's marker value exceeding a threshold. Although traditional regression methods may assess the effect of the marker and treatment on outcomes, it is appealing to quantify more directly the potential impact on the population of using the marker to select treatment. A useful tool is the selection impact (SI) curve proposed by Song and Pepe (2004, \textit{Biometrics} \textbf{60}, 874--883) for binary outcomes. However, this approach does not deal with continuous outcomes, nor …

Angiogenic Biomarkers For Risk Stratification In Women With Suspected Preeclampsia, Andreea Balan, Heather Young, Linda Ojo, Jennifer Keller, Sharon Maynard

Epidemiology Faculty Posters and Presentations

This poster presents the results of a single-center prospective cohort study of 315 pregnant women who presented to George Washington University Hospital Labor and Delivery service with a clinical suspicion of preeclampsia between February 2007 and November 2011. Informed consent was obtained. Baseline demographic information and medical history was collected on each patient including maternal age, ethnicity, body mass index, tobacco and other substance use, gestational age, medical problems and obstetric history. Serum samples were obtained from each enrolled subject within 24 hours of admission, and sFlt1, PlGF and sEng ELISA assays were performed in duplicate by a blinded laboratory …

A Novel Device For Cell-Cell Electrofusion, Justin T. Stewart

USF Tampa Graduate Theses and Dissertations

Cell transplantation therapy is a potentially powerful tool and can be used to replace defective cells with healthy cells. This offers the possibility of alleviating the destructive symptoms for many diseases such as Parkinson's disease, Alzheimer's disease, stroke, spinal cord trauma, Type I diabetes and many more. While there are many diseases that could be positively impacted from cell transplantation therapy, the focus of this research is insulin dependent, Type I Diabetes.

The Islets of Langerhans are composed of various types of cells located in the pancreas and are responsible for a variety of biochemical functions. Specifically, the beta Islet …

Statistical Models For Environmental And Health Sciences, Yong Xu

USF Tampa Graduate Theses and Dissertations

Statistical analysis and modeling are useful for understanding the behavior of different phenomena. In this study we will focus on two areas of applications: Global warming and cancer research. Global Warming is one of the major environmental challenge people face nowadays and cancer is one of the major health problem that people need to solve.

For Global Warming, we are interest to do research on two major contributable variables: Carbon dioxide (CO2) and atmosphere temperature. We will model carbon dioxide in the atmosphere data with a system of differential equations. We will develop a differential equation for each of six …

Analysis Of Differential Gene Expression And Alternative Splicing In The Liver And Gastrointestinal Tract In The Lactating Rat, Antony Thomas Athippozhy

University of Kentucky Doctoral Dissertations

Rat exon microarrays were utilized to detect changes in mRNA expression and alternative splicing in the liver, duodenum, jejunum, and ileum of the lactating rat when compared to age-matched virgin controls. Analysis of data at the level of gene expression revealed differential expression of genes involved in cholesterol biosynthesis in each tissue examined, suggesting increased Sterol Response Element Binding Protein activity. We also detected decreased mRNA from components of the T-cell signaling pathway in the jejunum and ileum. We characterized expression of solute carrier and adenosine triphosphate binding cassette proteins. In addition to characterizing genes by pathway, we have also …

Gender Differences In Lung Cancer Treatment And Survival, Margaret Anne Kowski

USF Tampa Graduate Theses and Dissertations

The objectives of this research were to test treatment and survival differences between women and men with lung cancer as there is minimal investigation in the literature. Three research questions were developed with statistical testing for gender differences based on similar cancer type, stage, treatment assignment and survival. Data for 44,863 primary lung cancer cases were collected from eight U.S. state-based cancer registries to investigate the research questions. The lung cancer incidence data included the morphological cell-types of adenocarcinoma (AC); squamous cell carcinoma (SCC); large cell carcinoma (LCC) and small cell carcinoma (SCC). Stage, grade, treatment type, as well as, …

Minimum Description Length Measures Of Evidence For Enrichment, Zhenyu Yang, David R. Bickel

COBRA Preprint Series

In order to functionally interpret differentially expressed genes or other discovered features, researchers seek to detect enrichment in the form of overrepresentation of discovered features associated with a biological process. Most enrichment methods treat the p-value as the measure of evidence using a statistical test such as the binomial test, Fisher's exact test or the hypergeometric test. However, the p-value is not interpretable as a measure of evidence apart from adjustments in light of the sample size. As a measure of evidence supporting one hypothesis over the other, the Bayes factor (BF) overcomes this drawback of the p-value but lacks …

Predicting Treatment Efficacy Via Quantitative Mri: A Bayesian Joint Model, Jincao Wu, Tim Johnson

The University of Michigan Department of Biostatistics Working Paper Series

The prognosis for patients with high-grade gliomas is poor, with a median survival of one year. Treatment efficacy assessment is typically unavailable until 5{6 months post diagnosis. Investigators hypothesize that quantitative MRI (qMRI) can assess treatment efficacy three weeks after therapy starts, thereby allowing salvage treatments to begin earlier. The purpose of this work is to build a predictive model of treatment efficacy using qMRI data and to assess its performance. The outcome is one-year survival status. We propose a joint, two-stage Bayesian model. In stage I, we smooth the image data with a multivariate spatio-temporal pairwise dierence prior. We …

Coronary Heart Disease Mortality And Long-Term Exposure To Ambient Particulate Air Pollutants In Elderly Nonsmoking California Residents, Lie Hong Chen

Loma Linda University Electronic Theses, Dissertations & Projects

The purpose of this study is to assess the effect of long-term concentrations of ambient PM on risks of all causes, cardiopulmonary, coronary heart disease (CHD), total cancer, and any mention of nonmalignant respiratory disease (NMRD) mortality.

The health effects of long-term ambient air pollution have been studied with up to 30 years of follow-up in the AHSMOG cohort, a cohort of 6,338 nonsmoking white California adults. Monthly concentrations of ambient air pollutants [particulate matter(PMio), Ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2) or particulate matter

In the AHSMOG cohort, each increment of 10 |ig/m3 in PMio in two-pollutant models …

The Determinants Of Colorectal Cancer Survival Disparities In Nevada, Lucas N. Wassira

UNLV Theses, Dissertations, Professional Papers, and Capstones

Different population groups across Nevada and throughout the United States suffer disproportionately from colorectal cancer and its after-effects. Overcoming cancer health disparities is important for lessening the burden of cancer. There has been an overall decline in the incidence of and mortality from colorectal cancer (CRC). This is likely due, in part, to the increasing use of screening procedures such as Fecal Occult Blood Test (FOBT) and/or endoscopy, which can reduce the risk of CRC mortality by fifty percent. Nevertheless, screening procedures are routinely used by only fifty percent of Americans aged fifty years and older. Despite overall mortality decreasing …

Spatial Epidemiology Of Birth Defects In The United States And The State Of Utah Using Geographic Information Systems And Spatial Statistics, Samson Y. Gebreab

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Oral clefts are the most common form of birth defects in the United States (US) and the State of Utah has among the highest prevalence of oral clefts in the nation. The overall objective of this dissertation was to examine the spatial distribution of oral clefts and their linkage with a broad range of demographic, behavioral, social, economic, and environmental risk factors through the application of Geographic Information Systems (GIS) and spatial statistics. Using innovative linked micromaps plots, we investigated the geographic patterns of oral clefts occurrence from 1998 to 2002 and their relationships with maternal smoking rates and proportion …

Asymptotic Theory For Cross-Validated Targeted Maximum Likelihood Estimation, Wenjing Zheng, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider a targeted maximum likelihood estimator of a path-wise differentiable parameter of the data generating distribution in a semi-parametric model based on observing n independent and identically distributed observations. The targeted maximum likelihood estimator (TMLE) uses V-fold sample splitting for the initial estimator in order to make the TMLE maximally robust in its bias reduction step. We prove a general theorem that states asymptotic efficiency (and thereby regularity) of the targeted maximum likelihood estimator when the initial estimator is consistent and a second order term converges to zero in probability at a rate faster than the square root of …

Observational Study And Individualized Antiretroviral Therapy Initiation Rules For Reducing Cancer Incidence In Hiv-Infected Patients, Romain Neugebauer, Michael J. Silverberg, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Targeted Maximum Likelihood Learning (TMLL) has been proposed as a general estimation methodology that can, in particular, be applied to draw causal inferences based on marginal structural modeling with observational data using either a point treatment approach (all confounders are assumed not to be affected by the exposure(s) of interest) or a longitudinal data approach (some confounders may be affected by one of the exposures of interest). While formal development of TMLL has included road maps for applications in longitudinal data approaches, real-life implementations have been restricted to studies based on a point treatment approach. In this article, we illustrate …

Inferential Methods For High-Throughput Methylation Data, Maria Capparuccini

Theses and Dissertations

The role of abnormal DNA methylation in the progression of disease is a growing area of research that relies upon the establishment of sound statistical methods. The common method for declaring there is differential methylation between two groups at a given CpG site, as summarized by the difference between proportions methylated db=b1-b2, has been through use of a Filtered Two Sample t-test, using the recommended filter of 0.17 (Bibikova et al., 2006b). In this dissertation, we performed a re-analysis of the data used in recommending the threshold by fitting a mixed-effects ANOVA model. It was determined that the 0.17 filter …

Power And Sample Size For Three-Level Cluster Designs, Tina Cunningham

Theses and Dissertations

Over the past few decades, Cluster Randomized Trials (CRT) have become a design of choice in many research areas. One of the most critical issues in planning a CRT is to ensure that the study design is sensitive enough to capture the intervention effect. The assessment of power and sample size in such studies is often faced with many challenges due to several methodological difficulties. While studies on power and sample size for cluster designs with one and two levels are abundant, the evaluation of required sample size for three-level designs has been generally overlooked. First, the nesting effect introduces …

Stereotype Logit Models For High Dimensional Data, Andre Williams

Theses and Dissertations

Gene expression studies are of growing importance in the field of medicine. In fact, subtypes within the same disease have been shown to have differing gene expression profiles (Golub et al., 1999). Often, researchers are interested in differentiating a disease by a categorical classification indicative of disease progression. For example, it may be of interest to identify genes that are associated with progression and to accurately predict the state of progression using gene expression data. One challenge when modeling microarray gene expression data is that there are more genes (variables) than there are observations. In addition, the genes usually demonstrate …

Mengukur Kualitas Hidup Anak, Toha Muhaimin

Kesmas

Kata kualitas hidup sering dihubungkan dengan pembangunan, khususnya pembangunan manusia, yang sering dikaitkan dengan kondisi seseorang baik dalam keadaan sehat maupun sakit, untuk menunjukkan aktivitas fisik, atau kondisi seseorang dalam hidup sehari-harinya. Sebagian orang mengkaitkan istilah kualitas hidup dengan kondisi sejauh mana terpenuhinya kebutuhan dasar untuk hidup seperti sandang, pangan, papan dan pendidikan pada seseorang. Oleh karena itu, banyak penelitian mengukur kualitas hidup dengan instrumen yang berbeda-beda, termasuk mengukur kualitas hidup anak dan banyak instrumen yang telah dikembangkan. Tulisan ini mencoba membahas pengertian kualitas hidup dan cara mengukurnya, terutama pada anak. Belum ada konsensus mengukur atau menggambarkan definisi konseptual kualitas …

Modeling Functional Data With Spatially Heterogeneous Shape Characteristics, Ana-Maria Staicu, Ciprian M. Crainiceanu, Daniel S. Reich, David Ruppert

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set …