Browsing Biostatistics by Title
Now showing items 103-122 of 215
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Latent Class and Latent Profile Analysis in Medical Diagnosis and Prognosis
(2013-11-14)Evaluating test accuracy is an important topic in medical diagnosis and prognosis. Accuracy information is necessary for care-givers to make well-informed decisions; it also helps researchers to select better diagnostic ... -
Latent Continuous Time Markov Chains for Partially-Observed Multistate Disease Processes
(2014-04-30)A disease process refers to a patient's traversal over time through a disease with multiple discrete states. Multistate models are powerful tools used to describe the dynamics of disease processes. Clinical study settings ... -
Leveraging Decision Theory to Address Statistical Challenges and Regression Under Additive Nonignorable Missingness
This dissertation is composed of three mutually exclusive projects, presented in individual chapters. The first chapter summarizes a novel method for regression estimation under nonignorable missingness. The latter two ... -
Local Estimation of Patient Prognosis
Statistical methods that can provide patients and their healthcare providers with individual predictions are needed so that informed medical decisions can be made. Ideally an individual prediction would display the full ... -
A Marginal Structural Cox Model Based Analysis Of The Comparative Effectiveness Of Two Dialysis Therapies
The Institute of Medicine identified comparing the effectiveness of renal replacement therapies as the only kidney-disease related topic among the top 100 initial national priorities for comparative effectiveness research. ... -
Marginalizable mixed effect models for clustered binary, categorical and survival data
In this thesis, I propose new models for clustered data, design estimators of covariate effects, implement model inference algorithms, and show asymptotic properties of my estimators, including consistency and asymptotic ... -
Measurement Error in Microbiome Sequencing Experiments: Statistical and Scientific Considerations
Next-generation sequencing (NGS)methods have become an essential tool in the study of complex microbial communities known as microbiomes. Because their near ubiquity, such communities have been the focus of substantial ... -
Mediation Analysis with Complex Intermediate Causal Structure
My doctoral research is oriented around causal inference, specifically causal mediation anal ysis. Roughly, it can be divided into two parts: (1) understanding and resolving conceptual issues in causal problems, and (2) ... -
Methodology for Examining Differential Rates of Change for Longitudinal Data
(2013-04-17)A common objective for longitudinal studies is to characterize differences in the rate of growth, or rate of change of an outcome across covariate-defined groups. The statistical challenges and potential extensions of ... -
Methods and Theory for Nonparametric Inference In High-dimensional Settings
This dissertation addresses nonparametric estimation and inference problems of graphical modeling, linear association assessment, and matrix completion. First, we introduce a flexible framework for nonparametric graphical ... -
Methods for Agnostic Statistical Inference
A traditional goal of parametric statistics is to estimate some or all of a data-generating model's finite set of parameters, thereby turning data into scientific insights. Point estimates of parameters, and corresponding ... -
Methods for Causal Inference in Randomized Trials with Multiple Versions of Control and Noncompliance, with an Application to Behavioral Intervention Trials
Behavioral therapies are a class of interventions with a wide array of applications.Because of the complicated nature of these interventions, however, conducting randomized controlled trials of these interventions ... -
Methods for Coherent and Exact Inference
This dissertation provides methods for coherent and exact inference for two types of problems in statistics. The first problem provides coherent criteria for the testing of nested interval null hypothesis. The second and ... -
Methods for Confounding Adjustment and High-Dimensional Environmental Exposures
Environmental exposures have complex multivariate relationships with one another and with geographic, anthropogenic, social, and physiological factors. This dissertation comprises methods for addressing the confounding and ... -
Methods for describing the time-varying predictive performance of survival models
In this dissertation we develop new methods for quantifying the predictive performance of a survival model at different times. We broadly categorize predictive performance into either calibration or discrimination, and ... -
Methods for detection of interactions with multiple components
(2013-07-25)In genetic association studies, it is typically thought that important insights will be obtained through joint modeling of genetic variants and environmental variables. However, weak effect of gene-environment interactions, ... -
Methods for Estimating Causal Effects of Treatment in Randomized Controlled Trials with Simultaneous Provider and Subject Noncompliance
Subject noncompliance is a common problem in the analysis of randomized controlled trials (RCTs); with cognitive behavioral interventions, the addition of provider noncompliance further complicates making causal inference. ... -
Methods for estimation and evaluation of marker-guided treatment rules based on multivariate marker panels
Due to vast heterogeneity in patients' responses, a uniformly preferred treatment is often not available. In such cases, clinical practice may be enhanced by use of person-level information that could guide treatment choice ... -
Methods for Hypothesis Testing in Animal Carcinogenicity Experiments
Animal carcinogenicity experiments are conducted by private entities and government agencies to investigate whether a substance causes cancer. Since most tumors are occult and it is necessary to conduct a necropsy to detect ... -
Methods for Risk Markers that Incorporate Clinical Utility
Risk markers are often used to help make clinical decisions. In this dissertation, we focus on developing statistical methods that account for the utility of a risk marker. We address problems of individualized decision-making, ...