Browsing by Department "Biostatistics"
Now showing items 1-20 of 62
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(2020-11-10)Department: BiostatisticsAutism 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 ...
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(2018-07-22)Department: BiostatisticsOur 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 ...
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(2017-06-20)Department: BiostatisticsOncology 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 ...
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(2020-09-18)Department: BiostatisticsIn 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 ...
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(2016-07-25)Department: BiostatisticsNonstationary 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. ...
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(2022-11-18)Department: BiostatisticsIn 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 ...
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(2019-11-21)Department: BiostatisticsIn 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 ...
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(2018-09-19)Department: BiostatisticsAs 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 ...
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(2016-12-13)Department: BiostatisticsThis 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 ...
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(2018-11-30)Department: BiostatisticsRisk 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. ...
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(2015-07-21)Department: BiostatisticsBIOSTATISTICS 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 ...
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(2022-05-10)Department: BiostatisticsBayesian 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 ...
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(2018-11-27)Department: BiostatisticsThis 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 ...
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(2017-08-03)Department: BiostatisticsIn 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 ...
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(2020-07-19)Department: BiostatisticsWhen 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 ...
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(2021-08-13)Department: BiostatisticsTime-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 ...
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(2017-09-21)Department: BiostatisticsPre-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 ...
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(2023-06-28)Department: BiostatisticsElectronic 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 ...
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(2023-06-28)Department: BiostatisticsElectronic 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 ...
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Development of prognostic model for breast cancer in Shanghai Breast Cancer Survival Study (SBCSS) (2015-07-23)Department: BiostatisticsWe 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, ...