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Electronic Books at the Vanderbilt Library: Theses and Dissertations

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ProQuest Dissertations

Dissertations and Theses Full Text is one database within ProQuest Central which contains searchable citations to dissertations and theses from around the world from 1861 to the present. Over 1.2 million of these dissertations are now available to the Vanderbilt community in a downloadable PDF format.

Vanderbilt Electronic Theses and Dissertations

Vanderbilt ETD (Electronic Theses and Dissertations)

The Library Catalog records for those Vanderbilt theses and dissertations which are available electronically will have a link at the top of the record which will take the reader to a title page listing the committee members’ names, defense date, and similar information.   At the bottom of the title page is a link to a pdf of the entire work.

These have no DRM and can be annotated and printed at will.

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• Last Updated: Apr 6, 2021 11:35 AM
• URL: https://researchguides.library.vanderbilt.edu/ebooks

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Browsing Electronic Theses and Dissertations by Department "Biostatistics"

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• A Bayesian framework to integrate genomic annotations for identification of Autism risk genes  Ji, Ying; 0000-0001-5691-1303 ( 2020-11-10 ) Department: Biostatistics Autism spectrum disorder (ASD) is a group of complex neurodevelopment disorders with a strong genetic basis. Large scale sequencing studies have provided strong evidence for dozens of ASD risk genes. However, it is estimated ...
• A Bayesian Model for Brain Network Functional Connectivity using PyMC3  Wang, Rui ( 2018-07-22 ) Department: Biostatistics Our brain network, as a complex integrative system, consists of many different regions. Each region has its own task and function and simultaneously shares structural and functional information. With the developed imaging ...
• A Comparison of Approaches for Unplanned Sample Size Changes in Phase II Clinical Trials  Olson, Molly Ann ( 2017-06-20 ) Department: Biostatistics Oncology phase II clinical trials are used to evaluate the initial effect of a new regimen to determine if there warrants further study in a phase III clinical trial. Two-stage designs with an early futility stop are ...
• A Data Adaptive Estimator for the Average Treatment Effect Based on Inverse Probability Weighting  Gao, Yue; 0000-0002-0440-4497 ( 2020-09-18 ) Department: Biostatistics In observational studies, the propensity score method is often used as an approach to handle the confounding by indication bias. Among other methods, inverse probability of treatment weighting uses weights based on the ...
• A Modified Random Forest Kernel for Highly Nonstationary Gaussian Process Regression with Application to Clinical Data  VanHouten, Jacob Paul ( 2016-07-25 ) Department: Biostatistics Nonstationary Gaussian process regression can be used to transform irregularly episodic and noisy measurements into continuous probability densities to make them more compatible with standard machine learning algorithms. ...
• A Simulated Exploration of Alternatives to Standard Expansion Cohorts in Phase 1 Trials  Jacobs, Justin Leon; 0000-0002-5621-5962 ( 2022-11-18 ) Department: Biostatistics In phase 1 clinical trials, dose escalation is an iterative process whereby a maximum tolerated dose (MTD) is identified for subsequent testing. Patients are treated with escalating dose levels to determine which may result ...
• A statistical critique of normalization methods in basic science research  Halvorson, Alese Erin ( 2019-11-21 ) Department: Biostatistics In basic science experiments, there is a tendency to utilize group-specific control measures in the creation of normalized quantities for comparison across groups. The desire is to compare relative knockout and wild-type ...
• Advanced Statistical Techniques in DW-MRI and fMRI Data Analysis  Hainline, Allison Elisabeth ( 2018-09-19 ) Department: Biostatistics As neuroimaging studies become more numerous and data are increasingly available, the need for improved understanding of the statistical properties of such data increases as well. In this dissertation, we focus on the ...
• Aspects of Causal Inference within the Evenly Matchable Population: The Average Treatment Effect on the Evenly Matchable Units, Visually Guided Cohort Selection, and Bagged One-to-One Matching  Samuels, Lauren Ruth ( 2016-12-13 ) Department: Biostatistics This dissertation consists of three papers related to causal inference about the evenly matchable units in observational studies of treatment effect. The first paper begins by defining the evenly matchable units in a sample ...
• Assessing Risk Score Calculation in the Presence of Uncollected Risk Factors  Toll, Alice Elizabeth ( 2018-11-30 ) Department: Biostatistics Risk scores developed from risk prediction models assist clinicians and patients as a decision support tool. Additionally, well supported risk scores can also be used as an adjusting risk factor in clinical research. ...
• Assessment of Propensity Score Performance in Small Samples  Peterson, Emily Nancy ( 2015-07-21 ) Department: Biostatistics BIOSTATISTICS ASSESSMENT OF PROPENSITY SCORE PERFORMANCE IN SMALL SAMPLES EMILY PETERSON Thesis under the direction of Professor Tatsuki Koyama In observational studies, treatment selection is determined by the ...
• Bayesian Methods for Cumulative Probability Models and Population Pharmacokinetic Models  James, Nathan Thomas; 0000-0001-7079-9151 ( 2022-05-10 ) Department: Biostatistics Bayesian methods offer many advantages in clinical trials, healthcare evaluation, and drug development, but their usage lags that of classical 'frequentist' methods. While some of this lag is related to philosophical ...
• Bayesian Transformation Models for Multivariate Survival Analysis with Applications in Large Data  Schlueter, David Jeffrey ( 2018-11-27 ) Department: Biostatistics This dissertation broadly focuses on the advancement and extension of Bayesian methods for multivariate survival analysis with applications in larger data settings. Increased sample information allows researchers to develop ...
• Conditional Associations with Big Data: Estimating Adjusted Rank Correlations in the Electronic Health Record  Fu, Lingjun ( 2017-08-03 ) Department: Biostatistics In this thesis, we apply and adapt a new method to assess conditional associations in a large dataset from the Vanderbilt University Medical Center Electronic Health Record (EHR). We estimate pairwise rank correlations ...
• Coping With Complexities in High Dimensional Data: PheWAS in EMR and Statistical Inference in fMRI Data  Lin, Ya-Chen; 0000-0003-3660-4570 ( 2020-07-19 ) Department: Biostatistics When conducting analyses on high dimensional data, one could face statistical difficulties due to large dimensionality and the noisy nature of the data. In this dissertation, we specifically look into potential complexities ...
• Cumulative Probability Models for Semiparametric G-Computation  Birdrow, Caroline Isabelle; 0000-0003-0577-9183 ( 2021-08-13 ) Department: Biostatistics Time-varying confounding is a commonly encountered challenge in longitudinal observational studies that seek to evaluate the causal effect of a time-dependent treatment. Because a time-varying confounder is influenced by ...
• Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies  Mercaldo, Nathaniel David ( 2017-09-21 ) Department: Biostatistics Pre-existing cohort data (e.g., electronic health records) are being increasingly available, and the need for novel and efficient uses of these data is paramount due to resource constraints. This dissertation consists of ...
• Design and Analysis Methods for Modern Biomedical Studies with Longitudinal Outcomes  Di Gravio, Chiara; 0000-0002-0532-267X ( 2023-06-28 ) Department: Biostatistics Electronic health records, existing cohort studies and clinical trials provide easily accessible data on outcome and covariates (e.g., disease status, vital signs) for most or all study subjects. However, many scientific ...
• Development of prognostic model for breast cancer in Shanghai Breast Cancer Survival Study (SBCSS)  Fan, Run ( 2015-07-23 ) Department: Biostatistics We developed prognostic models to predict five-year overall survival (OS), ten-year overall survival (OS), and five-year relapse-free survival (RFS) from Shanghai Breast Cancer Survival Study (SBCSS). SBCSS is a large, ...

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