Browsing by Subject "Biostatistics"
Now showing items 1-20 of 28
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Assessing Interchangeability among Raters with Continuous Outcomes in Agreement Studies
(2020)In various medical settings, new raters are available to take measurements for evaluations of medical conditions. One may want to use new and existing raters simultaneously or replace the existing raters with the new one ... -
B cells and the Antibody-Dependent Immune Response in Cancer and Infection
(2015)B cells and humoral immunity are critical components of an effective immune response. However, B cells are also a significant driver of a variety of autoimmune diseases and can also become malignant. Antibody-mediated B ... -
Bayesian interaction estimation with high-dimensional dependent predictors
(2021)Humans are constantly exposed to mixtures of different chemicals arising from environmental contamination. While certain compounds, such as heavy metals and mercury, are well known to be toxic, there are many complex mixtures ... -
Bayesian Kernel Models for Statistical Genetics and Cancer Genomics
(2017)The main contribution of this thesis is to examine the utility of kernel regression ap- proaches and variance component models for solving complex problems in statistical genetics and molecular biology. Many of these types ... -
Deriving Real-World Insights From Real-World Data: Biostatistics to the Rescue.
(Annals of internal medicine, 2018-09) -
Design and Monitoring of Clinical Trials with Clustered Time-to-Event Endpoint
(2020)Many clinical trials are involved with clustered data that consists of groups (called clusters) of nested subjects (called subunits). Observations from subunits within each cluster tend to be positively correlated due to ... -
Efficient analysis of complex, multimodal genomic data
(2016)Our primary goal is to better understand complex diseases using statistically disciplined approaches. As multi-modal data is streaming out of consortium projects like Genotype-Tissue Expression (GTEx) project, which aims ... -
EVALUATING AND INTERPRETING MACHINE LEARNING OUTPUTS IN GENOMICS DATA
(2022)In my dissertation, we have developed statistical and computational tools to evaluate and interpret machine learning outputs in genomics data. The first two projects focus on single-cell RNA-sequencing (scRNA-seq) data. ... -
Extending Probabilistic Record Linkage
(2020)Probabilistic record linkage is the task of combining multiple data sources for statistical analysis by identifying records pertaining to the same individual in different databases. The need to perform probabilistic record ... -
Gaussian Process-Based Models for Clinical Time Series in Healthcare
(2018)Clinical prediction models offer the ability to help physicians make better data-driven decisions that can improve patient outcomes. Given the wealth of data available with the widespread adoption of electronic health records, ... -
Gene set-based Signal-Detection Analyses with Goodness-of-Fit Statistics and Their Application in Complex Diseases
(2019)Rare diseases are difficult to diagnose and uncertain to treat. The identification of specific genes associated with particular rare diseases and phenotypes can provide insight into the mechanism of certain rare disease ... -
Genetic Analysis of Gulf War illness: Phenotype Development, GWAS, and Gene-Environment Interaction
(2022)Veterans who served in the 1990-1991 Gulf War experience debilitating chronic symptoms at extremely high rates. In the 30 years since the Gulf War, many researchers have worked to identify the cause and biological pathway ... -
Genetic and Environmental Constraints on Developmental Systems: Towards Predicting Genetic Responses to Climate Change in Sea Urchins
(2012)Many factors, including gene networks, developmental processes, and the environment mediate the link between the activity of genes and complex phenotypes in higher organisms. While genetic variants are the raw material for ... -
Improving Clinical Prediction Models with Statistical Representation Learning
(2021)This dissertation studies novel statistical machine learning approaches for healthcare risk prediction applications in the presence of challenging scenarios, such as rare events, noisy observations, data imbalance, missingness ... -
Interfaces between Bayesian and Frequentist Multiplte Testing
(2015)This thesis investigates frequentist properties of Bayesian multiple testing procedures in a variety of scenarios and depicts the asymptotic behaviors of Bayesian methods. Both Bayesian and frequentist approaches to multiplicity ... -
Machine Learning for Uncertainty with Application to Causal Inference
(2022)Effective decision making requires understanding the uncertainty inherent in a problem. This covers a wide scope in statistics, from deriving an estimator to training a predictive model. In this thesis, I will spend three ... -
Marginal Methods for the Design and Analysis of Cluster Randomized Trials and Related Studies
(2022)Cluster randomized trials (CRTs) are used to study the effectiveness of complex or community-level interventions across a diverse range of contexts. These contexts present a range of logistical and statistical challenges ... -
Methods for Comparative Analysis of Chromatin Accessibility and Gene Expression, With Applications to Cellular Reprogramming
(2018)Cellular reprogramming processes remain poorly characterized at the level of genome- wide chromatin and gene expression changes. Specifically, the extent to which re- programmed cells differ quantitatively from both the ... -
Multiple Testing Embedded in an Aggregation Tree With Applications to Omics Data
(2020)In my dissertation, I have developed computational methods for high dimensional inference, motivated by the analysis of omics data. This dissertation is divided into two parts. The first part of this dissertation is motivated ... -
Multiple Testing for Data with Ancillary Information
(2022)In my dissertation, I develop three powerful hierarchical multiple testing methods by accounting for ancillary information of data. In my first project, we develop a multiple testing framework named Distance Assisted Recursive ...
