subject:(biostatistics)

University of California, Berkeley

1. Tran, Linh Mai. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.

Degree: 2016, University of California, Berkeley

URL: http://pqdtopen.proquest.com/#viewpdf?dispub=10150887

This dissertation discusses the application and comparative performance of double robust estimators for estimating the intervention specific mean outcome in longitudinal settings with time-dependent confounding as well as the corresponding estimator variances. (Abstract shortened by ProQuest.)

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tran, L. M. (2016). Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. (Thesis). University of California, Berkeley. Retrieved from http://pqdtopen.proquest.com/#viewpdf?dispub=10150887

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Thesis, University of California, Berkeley. Accessed February 27, 2021. http://pqdtopen.proquest.com/#viewpdf?dispub=10150887.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Web. 27 Feb 2021.

Vancouver:

Tran LM. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. [Internet] [Thesis]. University of California, Berkeley; 2016. [cited 2021 Feb 27]. Available from: http://pqdtopen.proquest.com/#viewpdf?dispub=10150887.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tran LM. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. [Thesis]. University of California, Berkeley; 2016. Available from: http://pqdtopen.proquest.com/#viewpdf?dispub=10150887

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of California – Riverside

2. Che, Xiaohong. Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.

Degree: Applied Statistics, 2011, University of California – Riverside

URL: http://www.escholarship.org/uc/item/6j96r6pw

► Quantitative trait loci (QTL) mapping is one of the applications of statistics in genetics.This dissertation focuses two problems on QTL mapping which include a newpermutation… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Che, X. (2011). Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/6j96r6pw

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Che, Xiaohong. “Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.” 2011. Thesis, University of California – Riverside. Accessed February 27, 2021. http://www.escholarship.org/uc/item/6j96r6pw.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Che, Xiaohong. “Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.” 2011. Web. 27 Feb 2021.

Vancouver:

Che X. Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping. [Internet] [Thesis]. University of California – Riverside; 2011. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/6j96r6pw.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Che X. Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping. [Thesis]. University of California – Riverside; 2011. Available from: http://www.escholarship.org/uc/item/6j96r6pw

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

3. Qiu, Jiaheng. FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION.

Degree: Biostatistics, 2014, UCLA

URL: http://www.escholarship.org/uc/item/1cj4b854

► The theory of optimal experimental design provides insightful guidance on resource allocation for many dose-response studies and clinical trials. However, as more and more complicated… (more)

▼ The theory of optimal experimental design provides insightful guidance on resource allocation for many dose-response studies and clinical trials. However, as more and more complicated models are developed, finding optimal designs has become an increasingly difficult task; therefore, the availability of an efficient and easy-to-use algorithm to find optimal designs is important for both researchers and practitioners. In recent years, nature-inspired algorithms like Particle Swarm Optimization(PSO) have been successfully applied to many non-statistical disciplines, such as computer science and engineering, even though there is no unified theory to explain why PSO works so well. To date, there is virtually no work in the mainstream statistical literature that applies PSO to solve statistical problems.In my dissertation, I review PSO methodology and show it is an easy and effective algorithm to generate locally D- and c-optimal designs for a variety of nonlinear statistical models commonly used in biomedical studies. I develop a new version of PSO called Ultra-dimensional PSO (UPSO) to find D-optimal designs for multi-variable exponential and Poisson regression models with up to five variables and all pairwise interactions. I use the proposed novel search strategy to find minimally supported D-optimal designs and ascertain conditions under which such optimal designs exist for such models. A remarkable discovery in my work is that locally D-optimal designs for such models can have many more support points than the number of parameters in the model. This result is both new and interesting because almost all D-optimal designs have equal or just one or two more number of points than the the number of parameters in the mean response function, see the examples in monographs by Fedorov [1972], Atkinson Atkinson et al. [2007], and recent papers by in Yang and Stufken [2009], Yang [2010]. This discovery also disproves the conjecture by Wang et al. [2006] that for M-variable interaction model (M > 2), D-optimal designs are also minimally and equally supported and have a similar structure as D-optimal designs for 2-variable model.In addition to single objective optimal designs, I apply PSO to find optimal designs for estimating parameters and interesting characteristics continuation-ratio (CR) model with non-constant slopes. Such a model has a great potential in dose finding studies because it takes both efficacy and toxicity into consideration. The optimal design I am interested in constructing is a three-objective optimal design, which provides efficient estimates for efficacy, adverse effect and all parameters in the CR model. This work is quite new because there are virtually no three-objective designs for a trinomial model reported in the literature. Through multiple objective efficiency plots, practitioners can construct the desired compound optimal design by selecting appropriate weighted average of three optimal criteria in a more flexible and informative way.I also conduct simulation studies for parameters selection in…

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Qiu, J. (2014). FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1cj4b854

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Qiu, Jiaheng. “FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION.” 2014. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/1cj4b854.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Qiu, Jiaheng. “FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION.” 2014. Web. 27 Feb 2021.

Vancouver:

Qiu J. FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION. [Internet] [Thesis]. UCLA; 2014. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/1cj4b854.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Qiu J. FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/1cj4b854

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

4. Estes, Jason. Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis.

Degree: Biostatistics, 2015, UCLA

URL: http://www.escholarship.org/uc/item/03g42586

► In the first chapter of this work, we characterize the dynamics of cardiovascular event risk trajectories for patients on dialysis while conditioning on survival status… (more)

▼ In the first chapter of this work, we characterize the dynamics of cardiovascular event risk trajectories for patients on dialysis while conditioning on survival status via multiple time indices: (1) time since the start of dialysis, (2) time since the pivotal initial infection-related hospitalization and (3) the patient's age at the start of dialysis. This is achieved by using a new class of generalized multiple-index varying coefficient (GM-IVC) models utilizing a multiplicative structure and one-dimensional varying coefficient functions along each time and age index. We develop a two-step estimation procedure for the GM-IVC models based on local maximum likelihood, and report new insights on the dynamics of cardiovascular events risk among the dynamic cohort of survivors using the United States Renal Data System database, which collects data on nearly all patients with end-stage renal disease in the U.S.In the second chapter of this work, we develop time-varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection-related hospitalization. For this,we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL-GVCMs) for modeling time-varying effects in longitudinal data with substantial follow-up truncation by death. We compare and contrast partly and fully conditional PL-GVCMs in our aforementioned application and develop generalized likelihood ratio tests. In the third chapter of this work, we introduce a time-varying standardized dynamic ratio (SDR) to aid in the evaluation of a dialysis facility's performance with respect to patient readmission rates as a function of time that patients are on dialysis. The estimation of SDR consists of two steps. First, we model the dependence of readmission events on facilities and patient-level characteristics using a multilevel varying coefficient model (MVCM) with fixed facility time-varying effects, with or without subject random effects. Second, using results from the models, standardization is achieved by computing the ratio of the sum of the predicted number of 30-day readmissions to the sum of the predicted number of 30-day readmissions assuming a reference standard and given the case-mix in that facility. A challenging aspect of our data application is that the number of model parameters is very large, and the estimation of high-dimensional parameters is troublesome. To overcome this problem, we propose a Newton Rhapson algorithm for the MVCM without the random effects, and an approximate EM algorithm for the MVCM with random effects. We propose a test statistic to facilitate in the identification of facilities whose outcomes are outside of normal expectations, and obtain p-values using re-sampling and simulation techniques. Finally, our method of identifying outlier facilities involves converting the observed p-values to Z-statistics and using the empirical null distribution, which accounts for over dispersion in the data.

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Estes, J. (2015). Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/03g42586

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Estes, Jason. “Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis.” 2015. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/03g42586.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Estes, Jason. “Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis.” 2015. Web. 27 Feb 2021.

Vancouver:

Estes J. Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis. [Internet] [Thesis]. UCLA; 2015. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/03g42586.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Estes J. Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/03g42586

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

5. Lu, Xuyang. Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome.

Degree: Biostatistics, 2014, UCLA

URL: http://www.escholarship.org/uc/item/8223z6fp

► The method of instrumental variable (IV) analysis has been widely used in economics, epidemiology, and other fields to estimate the causal effects of intermediate covariates… (more)

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lu, X. (2014). Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/8223z6fp

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lu, Xuyang. “Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome.” 2014. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/8223z6fp.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lu, Xuyang. “Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome.” 2014. Web. 27 Feb 2021.

Vancouver:

Lu X. Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome. [Internet] [Thesis]. UCLA; 2014. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/8223z6fp.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lu X. Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/8223z6fp

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

6. Han, Eunjung. Addressing challenges for population genetic inference from next-generation sequencing.

Degree: Biostatistics, 2014, UCLA

URL: http://www.escholarship.org/uc/item/87k8j8gg

► Next-generation sequencing (NGS) data provides tremendous opportunities for making new discoveries in biology and medicine. However, a structure of NGS data poses many inherent challenges… (more)

▼ Next-generation sequencing (NGS) data provides tremendous opportunities for making new discoveries in biology and medicine. However, a structure of NGS data poses many inherent challenges - for example, reads have high error rates, read mapping is sometimes uncertain, and coverage is variable and in many cases low or completely absent. These challenges make accurate individual-level genotype calls difficult and make downstream analysis based on genotypes problematic if genotype uncertainty is not accounted for. In this dissertation, I present recent works addressing challenges that arise in the analysis of NGS data for population genetic inferences and and provide recommendations and guidelines to interpret such data with precision. Throughout this dissertation, I focus on estimating the site frequency spectrum (SFS). The distribution of allele frequencies across polymorphic sites, also known as the SFS, is of primary interest in population genetics. It is a complete summary of sequence variation at unlinked sites and more generally, its shape reflects underlying population genetic processes.First, I characterize biases that can arise inferring the SFS from low- to medium-coverage sequencing data and present a statistical method that can ameliorate such biases. I compare two approaches to estimate the SFS from sequencing data: one approach infers individual genotypes from aligned sequencing reads and then estimates the SFS based on the inferred genotypes (call-based approach) and the other approach directly estimates the SFS from aligned sequencing reads by maximum likelihood (direct estimation approach). I find that the SFS estimated by the direct estimation approach is unbiased even at low coverage, whereas the SFS by the call-based approach becomes biased as coverage decreases. The direction of the bias in the call-based approach depends on the pipeline to infer genotypes. Estimating genotypes by pooling individuals in a sample (multisample calling) results in underestimation of the number of rare variants, whereas estimating genotypes in each individual and merging them later (single-sample calling) leads to overestimation of rare variants. I characterize the impact of these biases on downstream analyses, such as demographic parameter estimation and genome-wide selection scans. This work highlights that depending on the pipeline used to infer the SFS, one can reach different conclusions in population genetic inference with the same data set. Thus, careful attention to the analysis pipeline and SFS estimation procedures is vital for population genetic inferences.Next, I describe a development of a novel algorithm that can speed-up the existing direct estimation method with the EM optimization. The existing method directly estimates the SFS from sequencing data by first computing site likelihood vectors (i.e. the likelihood a site has a each possible allele frequency conditional on observed sequence reads) using a dynamic programming (DP) algorithm. Although this method produces an accurate SFS, computing the site…

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Han, E. (2014). Addressing challenges for population genetic inference from next-generation sequencing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/87k8j8gg

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Han, Eunjung. “Addressing challenges for population genetic inference from next-generation sequencing.” 2014. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/87k8j8gg.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Han, Eunjung. “Addressing challenges for population genetic inference from next-generation sequencing.” 2014. Web. 27 Feb 2021.

Vancouver:

Han E. Addressing challenges for population genetic inference from next-generation sequencing. [Internet] [Thesis]. UCLA; 2014. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/87k8j8gg.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Han E. Addressing challenges for population genetic inference from next-generation sequencing. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/87k8j8gg

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of California – Berkeley

7. Tran, Linh Mai. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.

Degree: Biostatistics, 2016, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/4zj7w7wv

► This dissertation discusses the application and comparative performance of double robust estimators for estimating the intervention specific mean outcome in longitudinal settings with time-dependent confounding… (more)

▼ This dissertation discusses the application and comparative performance of double robust estimators for estimating the intervention specific mean outcome in longitudinal settings with time-dependent confounding as well as the corresponding estimator variances. Specifically, we focus on carefully defining target causal parameters to avoid known positivity issues, estimating these parameters using the asymptotically efficient and double robust targeted minimum loss-based estimation, comparing this to other double robust estimators of the same causal parameter, and estimating the corresponding variances in a way which demonstrates valid Type I errors while retaining statistical power. Chapter 1 begins by introducing the open problem in statistics. We present the International epidemiologic Databases to Evaluate AIDS, East Africa region (IeDEA-EA) cohort and the implementation of a low risk express care program implemented between 2007-2009. We continue in Chapter 2 by presenting the targeted learning road map for causal inference. This road map is applied, as a case study, to the IeDEA-EA cohort in evaluating the impact of the low risk express care program. Targeted minimum loss-based estimation is used to estimate the intervention specific mean outcome using data adaptive machine learning candidate estimators for the nuisance parameters. Practical issues are addressed, including carefully defining the causal parameters (and the corresponding causal contrasts) and remaining within the boundaries implied by the statistical model while using the machine learning algorithms. In Chapter 3, we compare additional estimators for the intervention specific mean outcome. The iterated conditional expectation estimator, inverse probability weighted estimator, augmented inverse probability weighted estimator, double robust iterated conditional expectation estimator, and targeted minimum loss-based estimator are presented. Additionally, variations on the double robust iterated conditional expectation estimator and targeted minimum loss-based estimator are reviewed and implemented. Simulations are conducted to analyze the finite sample performance of each estimator, in both correct and mis-specified models. The estimators are also applied to estimating the impact of enrollment into the low risk express care program in the IeDEA-EA cohort. Chapter 4 studies the estimation of estimator variance for estimators solving the efficient influence function. A robust approach of estimating the efficient influence function variance is presented, followed by approaches for estimating the derived expectation of the variance. This robust approach of estimating the EIF variance can be used to raise a red flag for unreliable statistical inference due to sparsity, thereby declaring that the target parameter is practically not identifiable from the data, and that the reported variance estimates (though large) will themselves be imprecise. We additionally present a bootstrap approach based on fitting the initial density of the data once, followed by a…

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tran, L. M. (2016). Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4zj7w7wv

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Thesis, University of California – Berkeley. Accessed February 27, 2021. http://www.escholarship.org/uc/item/4zj7w7wv.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Web. 27 Feb 2021.

Vancouver:

Tran LM. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. [Internet] [Thesis]. University of California – Berkeley; 2016. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/4zj7w7wv.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tran LM. Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment. [Thesis]. University of California – Berkeley; 2016. Available from: http://www.escholarship.org/uc/item/4zj7w7wv

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

8. Wu, Sheng. Optimal Design of Cluster Randomized Trials with Binary Outcomes.

Degree: Biostatistics, 2015, UCLA

URL: http://www.escholarship.org/uc/item/0c5588qv

► Cluster randomized trials (CRTs) are increasingly used in many fields including public health and medicine. We consider two-arm CRTs with binary outcomes with possibly unequal… (more)

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wu, S. (2015). Optimal Design of Cluster Randomized Trials with Binary Outcomes. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/0c5588qv

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wu, Sheng. “Optimal Design of Cluster Randomized Trials with Binary Outcomes.” 2015. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/0c5588qv.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wu, Sheng. “Optimal Design of Cluster Randomized Trials with Binary Outcomes.” 2015. Web. 27 Feb 2021.

Vancouver:

Wu S. Optimal Design of Cluster Randomized Trials with Binary Outcomes. [Internet] [Thesis]. UCLA; 2015. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/0c5588qv.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu S. Optimal Design of Cluster Randomized Trials with Binary Outcomes. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/0c5588qv

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of California – Berkeley

9. Polley, Eric. Super Learner.

Degree: Biostatistics, 2010, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/4qn0067v

► The super learner is a general loss-based learning method designed to find the optimal combination of a set of learners. The super learner framework is… (more)

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Polley, E. (2010). Super Learner. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4qn0067v

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Polley, Eric. “Super Learner.” 2010. Thesis, University of California – Berkeley. Accessed February 27, 2021. http://www.escholarship.org/uc/item/4qn0067v.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Polley, Eric. “Super Learner.” 2010. Web. 27 Feb 2021.

Vancouver:

Polley E. Super Learner. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/4qn0067v.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Polley E. Super Learner. [Thesis]. University of California – Berkeley; 2010. Available from: http://www.escholarship.org/uc/item/4qn0067v

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of California – Berkeley

10. Ritter, Stephan Johannes. Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data.

Degree: Biostatistics, 2013, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/600946rx

► Three add-on packages for the R statistical programming environment (R Core Team, 2013) are described, with simulations demonstrating performance gains and applications to real data.… (more)

Subjects/Keywords: Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Ritter, S. J. (2013). Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/600946rx

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Ritter, Stephan Johannes. “Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data.” 2013. Thesis, University of California – Berkeley. Accessed February 27, 2021. http://www.escholarship.org/uc/item/600946rx.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Ritter, Stephan Johannes. “Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data.” 2013. Web. 27 Feb 2021.

Vancouver:

Ritter SJ. Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/600946rx.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ritter SJ. Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/600946rx

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

11. Abdalla, Nada. Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene.

Degree: Biostatistics, 2018, UCLA

URL: http://www.escholarship.org/uc/item/89k1w808

► In industrial hygiene, prediction of a worker's exposure to chemical concentrations at the workplace is important for exposure management and prevention. The objective of this… (more)

▼ In industrial hygiene, prediction of a worker's exposure to chemical concentrations at the workplace is important for exposure management and prevention. The objective of this dissertation is to consider and address challenges in the statistical analyses of exposure datain industrial hygiene. We outline a flexible Bayesian frameworks for parameter inference and exposure prediction. In particular, we will focus on two applications of the Bayesian approach on exposure data. The rst application is spatial interpolation of chemical concentrations at new locations when measurements are available from coastlines, as is the case in coastal clean-up operations in oil spills. We present novel yet simple methodology for analyzing spatial data that is observed over a coastline. We demonstrate four dierent models using two different representations of the coast. The four models were demonstrated on simulated data and two of them were also demonstrated on a dataset from the GuLF STUDY. Our contribution here is to oer practicing hygienists and exposure assessors with a simple and easy method to implement Bayesian hierarchical models for analyzing and interpolating coastal chemical concentrations.The second application is inference and prediction of chemical concentrations at the workplace using state space models. Exposure assessment models are deterministic models that are usually derived from physical-chemical laws that explain the workplace under theoretically ideal conditions. We propose Bayesian parametric and nonparametric approaches for modeling exposure data in industrial hygiene using a state space model framework which combines information from observations, physical processes and prior knowledge. Posterior inference is obtained via easy implementable Markov chain Monte Carlo (MCMC) algorithms. The performance of the dierent methods will be studied on computer-simulated and controlled laboratory-generated data. We will consider three commonly used occupational exposure physical models varying in complexity.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Abdalla, N. (2018). Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/89k1w808

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Abdalla, Nada. “Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene.” 2018. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/89k1w808.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Abdalla, Nada. “Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene.” 2018. Web. 27 Feb 2021.

Vancouver:

Abdalla N. Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene. [Internet] [Thesis]. UCLA; 2018. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/89k1w808.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Abdalla N. Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene. [Thesis]. UCLA; 2018. Available from: http://www.escholarship.org/uc/item/89k1w808

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

UCLA

12. Gupta, Megha. Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity.

Degree: Clinical Research, 2017, UCLA

URL: http://www.escholarship.org/uc/item/37p7m7v0

► Objective: To determine if timely treatment within 60 minutes of confirmed diagnosis of severe maternal hypertension with antihypertensive medications was associated with reduction in severe… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Gupta, M. (2017). Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/37p7m7v0

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Gupta, Megha. “Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity.” 2017. Thesis, UCLA. Accessed February 27, 2021. http://www.escholarship.org/uc/item/37p7m7v0.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Gupta, Megha. “Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity.” 2017. Web. 27 Feb 2021.

Vancouver:

Gupta M. Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity. [Internet] [Thesis]. UCLA; 2017. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/37p7m7v0.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gupta M. Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/37p7m7v0

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Louisville

13. Gregg, Mary Elizabeth. A log rank test for clustered data under informative within-cluster group size.

Degree: MS, 2016, University of Louisville

URL: 10.18297/etd/2434 ; https://ir.library.louisville.edu/etd/2434

► The log rank test is a popular nonparametric test for comparing the marginal survival distribution of two groups. When data are organized within clusters… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Gregg, M. E. (2016). A log rank test for clustered data under informative within-cluster group size. (Masters Thesis). University of Louisville. Retrieved from 10.18297/etd/2434 ; https://ir.library.louisville.edu/etd/2434

Chicago Manual of Style (16^th Edition):

Gregg, Mary Elizabeth. “A log rank test for clustered data under informative within-cluster group size.” 2016. Masters Thesis, University of Louisville. Accessed February 27, 2021. 10.18297/etd/2434 ; https://ir.library.louisville.edu/etd/2434.

MLA Handbook (7^th Edition):

Gregg, Mary Elizabeth. “A log rank test for clustered data under informative within-cluster group size.” 2016. Web. 27 Feb 2021.

Vancouver:

Gregg ME. A log rank test for clustered data under informative within-cluster group size. [Internet] [Masters thesis]. University of Louisville; 2016. [cited 2021 Feb 27]. Available from: 10.18297/etd/2434 ; https://ir.library.louisville.edu/etd/2434.

Council of Science Editors:

Gregg ME. A log rank test for clustered data under informative within-cluster group size. [Masters Thesis]. University of Louisville; 2016. Available from: 10.18297/etd/2434 ; https://ir.library.louisville.edu/etd/2434

Boston University

14. Liu, Xuan. New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power.

Degree: PhD, Biostatistics, 2015, Boston University

URL: http://hdl.handle.net/2144/15700

► In superiority "exploratory" Phase II clinical trials, we often compare the efficacy of several doses of an experimental product versus a control group (often a… (more)

▼ In superiority "exploratory" Phase II clinical trials, we often compare the efficacy of several doses of an experimental product versus a control group (often a placebo). We then use the results from the Phase II to design the subsequent confirmatory superiority Phase III trial, and we use statistical methods in the Phase III trial to demonstrate that the "best" (most efficacious) dose selected from the Phase II study is superior to the control. The two phases are usually separate and independent: the Phase III trial does not incorporate patient data from Phase II except, again, in designing the Phase III trial. If we can combine data from the two phases into one design and use data from both phases to assess efficacy of the most efficacious dose of the experimental treatment versus control, we can potentially shorten the overall time of clinical development by reducing the overall sample size across Phase II and Phase III combined. This kind of design is the so-called Adaptive Seamless Designs (ASD). In this dissertation, we first review two commonly used combination approaches for the adaptive seamless designs. These approaches combine the stagewise p-values and apply the closed testing procedure to control the familywise error rate at the nominal level. Due to their complexity in both understanding and implementation, we propose an approach that uses a standard statistical test to compare treatments on the endpoint at the final analysis; we derive the distribution of the final test statistic and the critical value required to maintain Type I error rate at the nominal level Our simulation studies show our approach is comparable to the combination approaches in terms of Type I error rate and power. An extension to Denne's sample size re-estimation method is applied in order to estimate the final Phase III sample size required to maintain desired power, conditioned on Phase II results, when using our proposed adaptive seamless design statistical test. Simulation results demonstrate that the type I error rate and power are maintained at the desired level.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Liu, X. (2015). New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/15700

Chicago Manual of Style (16^th Edition):

Liu, Xuan. “New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power.” 2015. Doctoral Dissertation, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/15700.

MLA Handbook (7^th Edition):

Liu, Xuan. “New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power.” 2015. Web. 27 Feb 2021.

Vancouver:

Liu X. New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power. [Internet] [Doctoral dissertation]. Boston University; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/15700.

Council of Science Editors:

Liu X. New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power. [Doctoral Dissertation]. Boston University; 2015. Available from: http://hdl.handle.net/2144/15700

Boston University

15. Lohsen, Mark. Combined genome-wide association studies of cannabis dependence and personality traits.

Degree: 2015, Boston University

URL: http://hdl.handle.net/2144/16029

► BACKGROUND: Cannabis dependence (CaD) and component behaviors of personality are highly heritable, but the genetic basis of these traits is poorly understood. Since several attributes… (more)

▼ BACKGROUND: Cannabis dependence (CaD) and component behaviors of personality are highly heritable, but the genetic basis of these traits is poorly understood. Since several attributes of personality (e.g. neuroticism) are strongly correlated with cannabis use, we hypothesized that specific combined genetic underpinnings contribute to both CaD and to certain aspects of personality. METHODS: Personality was quantified with the Revised NEO Personality Inventory that asked questions from the five personality domains. Personality information was acquired from 1931 African Americans (AAs) and 1517 European Americans (EAs). CaD was measured as a summation of the seven binary DSM-IV diagnosis symptoms within a separate set of 1311 AAs and 2752 EAs in the NIH-funded "Study of Addiction: Genetics and Environment" (SAGE). Genome-wide association studies (GWAS) were performed after filtering out single-nucleotide polymorphisms (SNPs) with low minor allele frequency (MAF) and poor imputation quality. The personality trait was used as the outcome in the primary data set while CaD was used in the SAGE data set. Meta-analysis was used to combine the results for both traits within and across ethnic groups. Additionally, while honing in on the personality / CaD comparison, the analysis further investigated component facets of the NEO domain most strongly correlated to CaD. RESULTS: Genome-wide significant (GWS) results were obtained for EAs from the bivariate analysis of CaD paired with the extraversion domain (rs12534830, p=1.73E-08) near SEMA3D and paired with the vulnerability to stress facet, which is a component of the neuroticism domain (rs76021834, p=1.58E-08) within POR. GWS association was also observed with the vulnerability to stress facet considered as a single outcome in a SNP within the solute carrier gene SLC35F3 (rs12047995, p=3.55E-08) in the combined sample of AAs and EAs. DISCUSSION: Notable associations with both CaD and several personality traits include SNPs from multiple semaphorin genes whose protein products are axonal growth cone guidance molecules. These SNPs were either within or proximal to SEMA3A, SEMA3D, SEMA6A, or SEMA6D, which have links to schizophrenia, as discussed in many other studies. Further investigation in independent data sets is warranted to confirm the validity of these findings.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Lohsen, M. (2015). Combined genome-wide association studies of cannabis dependence and personality traits. (Thesis). Boston University. Retrieved from http://hdl.handle.net/2144/16029

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lohsen, Mark. “Combined genome-wide association studies of cannabis dependence and personality traits.” 2015. Thesis, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/16029.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lohsen, Mark. “Combined genome-wide association studies of cannabis dependence and personality traits.” 2015. Web. 27 Feb 2021.

Vancouver:

Lohsen M. Combined genome-wide association studies of cannabis dependence and personality traits. [Internet] [Thesis]. Boston University; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/16029.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lohsen M. Combined genome-wide association studies of cannabis dependence and personality traits. [Thesis]. Boston University; 2015. Available from: http://hdl.handle.net/2144/16029

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Boston University

16. Gao, Wei. Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits.

Degree: PhD, Biostatistics, 2015, Boston University

URL: http://hdl.handle.net/2144/15688

► Genetic loci identified by single variant association tests account for only a small proportion of the heritability for most complex traits and diseases. Part of… (more)

▼ Genetic loci identified by single variant association tests account for only a small proportion of the heritability for most complex traits and diseases. Part of the unexplained heritability may be due to rare variants and their interactions with environmental factors. Different strategies have been taken to increase the power to detect genetic associations, such as increasing the sample size by including related participants and meta-analyzing multiple studies. Longitudinal data or repeated measurements are often available in prospective cohort studies. For complex diseases, multiple traits are usually collected to characterize affected individuals. Many of the existing statistical methods can only be applied to the scenarios when each participant has one measurement of a single trait. To take full advantage of the data and further improve power, multiple measurements per individual may be included in the analysis when available. In this dissertation we develop statistical methods for rare variant association testing and gene by environment interaction analysis, and discuss gene-based meta-analysis for studies with different designs. First, we propose the generalized Sequence Kernel Association Test (genSKAT) to deal with rare variants, familial correlation, and repeated measurements or multiple traits. This is an extension of the original SKAT and family-based SKAT that accounts for correlation between multiple measurements within each individual. In the second part of this dissertation, we discuss methods to test for the presence of gene-environment interaction effects in the genSKAT framework. Finally, we evaluate genSKAT meta-analysis methods to combine different types of studies: samples of unrelated individuals with one observation per person or with multiple observations per person, and family samples with one observation per person or with multiple observations per person. Combining all these projects together, we contribute methodologies to detect rare variant associations by taking advantage of additional information, improve the chance to detect novel rare variant associations, and help in understanding the role that genetic factors play in various diseases and traits.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Gao, W. (2015). Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/15688

Chicago Manual of Style (16^th Edition):

Gao, Wei. “Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits.” 2015. Doctoral Dissertation, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/15688.

MLA Handbook (7^th Edition):

Gao, Wei. “Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits.” 2015. Web. 27 Feb 2021.

Vancouver:

Gao W. Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits. [Internet] [Doctoral dissertation]. Boston University; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/15688.

Council of Science Editors:

Gao W. Sequence Kernel Association Test, gene-environment interaction test, and meta-analysis for family samples with repeated measurements or multiple traits. [Doctoral Dissertation]. Boston University; 2015. Available from: http://hdl.handle.net/2144/15688

University of California – Berkeley

17. Mejia, Robin Krieger. Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador.

Degree: Biostatistics, 2016, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/4wc329w8

► In this dissertation, I examine two human right estimation problems. First, I assess data on child abductions from El Salvador's civil war. Between 1979 and… (more)

▼ In this dissertation, I examine two human right estimation problems. First, I assess data on child abductions from El Salvador's civil war. Between 1979 and 1992, El Salvador was wracked by conflict between leftist guerrilla groups and right-wing nationalist governments. One feature of the conflict was the abduction of children by government military forces, or the forced surrender of children to those same forces. Since 1994, La Asociación Pro-Búsqueda de Niñas y Niños Desaparecidos has investigated cases of these child abductions. To date, they have opened more than 950 cases and located nearly 400 abducted children (now, young adults). The organization remains active, and new cases come to light each year. In Chapter 2, I examine Pro Busqueda's data, assessing what can be said to date about the total as yet unknown number of abductions that occurred. I demonstrate that more abductions occurred than the number of currently known cases discuss capture-recapture estimates under a range of assumptions about the data available today. I then lay out a plan for updating estimates as new data becomes available.Then, I examine current data on deaths from the ongoing conflict in Syria. Early in the conflict, the United Nations Office of the High Commissioner for Refugees (UNOHCR) contracted with statisticians at the Human Rights Data Analysis Group (HRDAG) to analyze data from multiple human rights groups that were documenting deaths from the conflict there. HRDAG produced three reports from the United Nations and has maintained ongoing relationships with the local human rights groups that are collecting the raw data. HRDAG is now in the unusual position of possessing a series of multiple ``snapshots'' of each group's data, collected at a number of points between 2012 and 2016. Using those snapshots, I examine how each group's data is changing over time, and discuss how those changes can impact resulting estimates of unreported deaths, showing that the changes can result in estimates for a single governorate that vary by nearly 100,000. In addition, I take advantage of the large number of processed cases to assess the performance of a variety of classification algorithms in determining whether two records refer to the same individual.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Mejia, R. K. (2016). Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4wc329w8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mejia, Robin Krieger. “Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador.” 2016. Thesis, University of California – Berkeley. Accessed February 27, 2021. http://www.escholarship.org/uc/item/4wc329w8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mejia, Robin Krieger. “Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador.” 2016. Web. 27 Feb 2021.

Vancouver:

Mejia RK. Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador. [Internet] [Thesis]. University of California – Berkeley; 2016. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/4wc329w8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mejia RK. Estimating the size of unobserved populations in human rights: Problems in Syria and El Salvador. [Thesis]. University of California – Berkeley; 2016. Available from: http://www.escholarship.org/uc/item/4wc329w8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Harvard University

18. Snavely, Anna Catherine. Multivariate Data Analysis with Applications to Cancer.

Degree: PhD, Biostatistics, 2012, Harvard University

URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266

► Multivariate data is common in a wide range of settings. As data structures become increasingly complex, additional statistical tools are required to perform proper analyses.… (more)

▼ Multivariate data is common in a wide range of settings. As data structures become increasingly complex, additional statistical tools are required to perform proper analyses. In this dissertation we develop and evaluate methods for the analysis of multivariate data generated from cancer trials. In the first chapter we consider the analysis of clustered survival data that can arise from multicenter clinical trials. In particular, we review and compare marginal and conditional models numerically through simulations and discuss model selection techniques. A multicenter clinical trial of children with acute lymphoblastic leukemia is used to illustrate the findings. The second and third chapters both address the setting where multiple outcomes are collected when the outcome of interest cannot be measured directly. A head and neck cancer trial in which multiple outcomes were collected to measure dysphagia was the particular motivation for this part of the dissertation. Specifically, in the second chapter we propose a semiparametric latent variable transformation model that incorporates measurable outcomes of mixed types, including censored outcomes. This method extends traditional approaches by allowing the relationship between the measurable outcomes and latent variable to be unspecified, rendering more robust inference. Using this approach we can directly estimate the treatment (or other covariate) effect on the unobserved latent variable, enhancing interpretation. In the third chapter, the basic model from the second chapter is maintained, but additional parametric assumptions are made. This model still has the advantages of allowing for censored measurable outcomes and being able to estimate a treatment effect on the latent variable, but has the added advantage of good performance in a small data set. Together the methods proposed in the second and third chapters provide a comprehensive approach for the analysis of complex multiple outcomes data. Advisors/Committee Members: Harrington, David Paul (advisor).

Subjects/Keywords: biostatistics

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APA (6^th Edition):

Snavely, A. C. (2012). Multivariate Data Analysis with Applications to Cancer. (Doctoral Dissertation). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266

Chicago Manual of Style (16^th Edition):

Snavely, Anna Catherine. “Multivariate Data Analysis with Applications to Cancer.” 2012. Doctoral Dissertation, Harvard University. Accessed February 27, 2021. http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266.

MLA Handbook (7^th Edition):

Snavely, Anna Catherine. “Multivariate Data Analysis with Applications to Cancer.” 2012. Web. 27 Feb 2021.

Vancouver:

Snavely AC. Multivariate Data Analysis with Applications to Cancer. [Internet] [Doctoral dissertation]. Harvard University; 2012. [cited 2021 Feb 27]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266.

Council of Science Editors:

Snavely AC. Multivariate Data Analysis with Applications to Cancer. [Doctoral Dissertation]. Harvard University; 2012. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266

Harvard University

19. White, Richard. Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota.

Degree: PhD, Biostatistics, 2012, Harvard University

URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732

► Ethical clinical trials need both societal and personal equipoise. Recently, personal equipoise has been disturbed by the introduction of interim analyses; after an interim analysis… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

White, R. (2012). Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota. (Doctoral Dissertation). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732

Chicago Manual of Style (16^th Edition):

White, Richard. “Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota.” 2012. Doctoral Dissertation, Harvard University. Accessed February 27, 2021. http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732.

MLA Handbook (7^th Edition):

White, Richard. “Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota.” 2012. Web. 27 Feb 2021.

Vancouver:

White R. Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota. [Internet] [Doctoral dissertation]. Harvard University; 2012. [cited 2021 Feb 27]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732.

Council of Science Editors:

White R. Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota. [Doctoral Dissertation]. Harvard University; 2012. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732

Harvard University

20. Braun, Danielle. Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies.

Degree: PhD, Biostatistics, 2013, Harvard University

URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468

► The first part of this dissertation focuses on methods to adjust for measurement error in risk prediction models. In chapter one, we propose a nonparametric… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Braun, D. (2013). Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies. (Doctoral Dissertation). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468

Chicago Manual of Style (16^th Edition):

Braun, Danielle. “Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies.” 2013. Doctoral Dissertation, Harvard University. Accessed February 27, 2021. http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468.

MLA Handbook (7^th Edition):

Braun, Danielle. “Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies.” 2013. Web. 27 Feb 2021.

Vancouver:

Braun D. Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies. [Internet] [Doctoral dissertation]. Harvard University; 2013. [cited 2021 Feb 27]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468.

Council of Science Editors:

Braun D. Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies. [Doctoral Dissertation]. Harvard University; 2013. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468

Virginia Commonwealth University

21. Galadima, Hadiza I. Controlling for Confounding when Association is Quantified by Area Under the ROC Curve.

Degree: PhD, Biostatistics, 2015, Virginia Commonwealth University

URL: https://doi.org/10.25772/DY4E-D895 ; https://scholarscompass.vcu.edu/etd/3905

► In the medical literature, there has been an increased interest in evaluating association between exposure and outcomes using nonrandomized observational studies. However, because assignments… (more)

▼ In the medical literature, there has been an increased interest in evaluating association between exposure and outcomes using nonrandomized observational studies. However, because assignments to exposure are not done randomly in observational studies, comparisons of outcomes between exposed and non-exposed subjects must account for the effect of confounders. Propensity score methods have been widely used to control for confounding, when estimating exposure effect. Previous studies have shown that conditioning on the propensity score results in biased estimation of odds ratio and hazard ratio. However, there is a lack of research into the performance of propensity score methods for estimating the area under the ROC curve (AUC). In this dissertation, we propose AUC as measure of effect when outcomes are continuous. The AUC is interpreted as the probability that a randomly selected non-exposed subject has a better response than a randomly selected exposed subject. The aim of this research is to examine methods to control for confounding when association between exposure and outcomes is quantified by AUC. We look at the performance of the propensity score, including determining the optimal choice of variables for the propensity score model. Choices include covariates related to exposure group, covariates related to outcome, covariates related to both exposure and outcome, and all measured covariates. Additionally, we compare the propensity score approach to that of the conventional regression approach to adjust for AUC. We conduct a series of simulations to assess the performance of the methodology where the choice of the best estimator depends on bias, relative bias, mean squared error, and coverage of 95% confidence intervals. Furthermore, we examine the impact of model misspecification in conventional regression adjustment for AUC by incorrectly modelling the covariates in the data. These modelling errors include omitting covariates, dichotomizing continuous covariates, modelling quadratic covariates as linear, and excluding interactions terms from the model. Finally, a dataset from the shock research unit at the University of Southern California is used to illustrate the estimation of the adjusted AUC using the proposed approaches. Advisors/Committee Members: Donna K. McClish, Ph.D..

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Galadima, H. I. (2015). Controlling for Confounding when Association is Quantified by Area Under the ROC Curve. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/DY4E-D895 ; https://scholarscompass.vcu.edu/etd/3905

Chicago Manual of Style (16^th Edition):

Galadima, Hadiza I. “Controlling for Confounding when Association is Quantified by Area Under the ROC Curve.” 2015. Doctoral Dissertation, Virginia Commonwealth University. Accessed February 27, 2021. https://doi.org/10.25772/DY4E-D895 ; https://scholarscompass.vcu.edu/etd/3905.

MLA Handbook (7^th Edition):

Galadima, Hadiza I. “Controlling for Confounding when Association is Quantified by Area Under the ROC Curve.” 2015. Web. 27 Feb 2021.

Vancouver:

Galadima HI. Controlling for Confounding when Association is Quantified by Area Under the ROC Curve. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2015. [cited 2021 Feb 27]. Available from: https://doi.org/10.25772/DY4E-D895 ; https://scholarscompass.vcu.edu/etd/3905.

Council of Science Editors:

Galadima HI. Controlling for Confounding when Association is Quantified by Area Under the ROC Curve. [Doctoral Dissertation]. Virginia Commonwealth University; 2015. Available from: https://doi.org/10.25772/DY4E-D895 ; https://scholarscompass.vcu.edu/etd/3905

University of Iowa

22. Pugh, Melissa Anna Maria. A Bayesian approach to detect time-specific group differences between nonlinear temporal curves.

Degree: PhD, Biostatistics, 2016, University of Iowa

URL: https://ir.uiowa.edu/etd/5606

► The visual world paradigm is a tool that is widely used in the field of psycholinguistics to help investigate how people listen and understand… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Pugh, M. A. M. (2016). A Bayesian approach to detect time-specific group differences between nonlinear temporal curves. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/5606

Chicago Manual of Style (16^th Edition):

Pugh, Melissa Anna Maria. “A Bayesian approach to detect time-specific group differences between nonlinear temporal curves.” 2016. Doctoral Dissertation, University of Iowa. Accessed February 27, 2021. https://ir.uiowa.edu/etd/5606.

MLA Handbook (7^th Edition):

Pugh, Melissa Anna Maria. “A Bayesian approach to detect time-specific group differences between nonlinear temporal curves.” 2016. Web. 27 Feb 2021.

Vancouver:

Pugh MAM. A Bayesian approach to detect time-specific group differences between nonlinear temporal curves. [Internet] [Doctoral dissertation]. University of Iowa; 2016. [cited 2021 Feb 27]. Available from: https://ir.uiowa.edu/etd/5606.

Council of Science Editors:

Pugh MAM. A Bayesian approach to detect time-specific group differences between nonlinear temporal curves. [Doctoral Dissertation]. University of Iowa; 2016. Available from: https://ir.uiowa.edu/etd/5606

Boston University

23. Xue, Luting. Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants.

Degree: PhD, Biostatistics, 2016, Boston University

URL: http://hdl.handle.net/2144/19565

► Interaction is likely to play a signiﬁcant role in complex diseases, and various methods are available for identifying interactions between variants in genome-wide association studies… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Xue, L. (2016). Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/19565

Chicago Manual of Style (16^th Edition):

Xue, Luting. “Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants.” 2016. Doctoral Dissertation, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/19565.

MLA Handbook (7^th Edition):

Xue, Luting. “Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants.” 2016. Web. 27 Feb 2021.

Vancouver:

Xue L. Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants. [Internet] [Doctoral dissertation]. Boston University; 2016. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/19565.

Council of Science Editors:

Xue L. Evaluation and extension of a kernel-based method for gene-gene interaction tests of common variants. [Doctoral Dissertation]. Boston University; 2016. Available from: http://hdl.handle.net/2144/19565

Boston University

24. Kane, Elizabeth. Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms.

Degree: PhD, Biostatistics, 2017, Boston University

URL: http://hdl.handle.net/2144/27352

► The healthy aging index (HAI) is a score variable based on five clinical components. I assess how well it predicts mortality in a sample of… (more)

▼ The healthy aging index (HAI) is a score variable based on five clinical components. I assess how well it predicts mortality in a sample of older adults from the Framingham Heart Study (FHS). Over 30% of FHS participants have missing HAI across time; I investigate how well imputation methods perform in this setting. I run simulations to compare four methods of multiple imputation (MI) by fully conditional specification (FCS) and the complete case (CC) approach on estimation of means, correlations, and slopes of the HAI over time. I simulate multivariate normal data for each component of HAI at four time points, along with age and sex, using within and across-time correlation patterns at the percent of missing data seen in observed FHS data. My methods of MI are cross-sectional FCS (XFCS, imputation model uses other components at same time), longitudinal FCS (LFCS, uses same component at all times ignoring cross-component correlation), all FCS (AFCS, uses all components at all times) and 2-fold FCS (2fFCS, uses all components at current and adjacent times). I compare percent bias, confidence interval width, coverage probability and relative efficiency for three mechanisms of missing data (MCAR,MAR,MNAR), two sample sizes (n=1000,100), and two numbers of imputed datasets (m=5,20). All longitudinal methods (not XFCS) yield nearly identical results with unbiased estimates of means, correlations and slopes. Increase in precision and relative efficiency is small when augmenting from 5 to 20 imputations. Finally, I compare the imputation methods and CC analysis in survival models using HAI as a time-dependent variable to predict mortality. I simulate HAI data as described above, time-to-death using piece-wise exponential models, and I impose type I and random censoring on 32% of observations. CC analysis reduces sample size by 10%, produces unbiased estimates, but inflates standard errors. The three longitudinal imputation methods introduce minimal bias (<5%) in the hazard ratio estimates, while reducing the standard error up to 10% compared with CC. Overall, I show that multiple imputation using longitudinal methods is beneficial in the setting of repeated measurements of a score variable. It works well in analyzing changes over time and in time-dependent survival analyses.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Kane, E. (2017). Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/27352

Chicago Manual of Style (16^th Edition):

Kane, Elizabeth. “Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms.” 2017. Doctoral Dissertation, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/27352.

MLA Handbook (7^th Edition):

Kane, Elizabeth. “Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms.” 2017. Web. 27 Feb 2021.

Vancouver:

Kane E. Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms. [Internet] [Doctoral dissertation]. Boston University; 2017. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/27352.

Council of Science Editors:

Kane E. Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms. [Doctoral Dissertation]. Boston University; 2017. Available from: http://hdl.handle.net/2144/27352

Boston University

25. Li, Shuo. Methods for correlated observations with applications to genetic association studies.

Degree: PhD, Biostatistics, 2019, Boston University

URL: http://hdl.handle.net/2144/38977

► Correlation is commonly present in genetic association studies and may yield incorrect inference when ignored. Hence, developing methods for properly analyzing correlated data is crucial.… (more)

▼ Correlation is commonly present in genetic association studies and may yield incorrect inference when ignored. Hence, developing methods for properly analyzing correlated data is crucial. However, there is a lack of analytical tools to answer certain questions because existing methods are not applicable when some model assumptions are violated. In this thesis, we propose three methods for correlated phenotypes, particularly correlation arising from family data. We first develop an iterated weighted linear mixed effects (IWLME) method to account for heteroscedasticity. We compare the model performance of IWLME with five other methods by simulation studies. When applying methods that ignore heteroscedasticity, the occurrence of heteroscedasticity results in lower power, but not excessive type I error. When heteroscedasticity is present, meta-analysis, linear mixed effects (LME) models in GENetic EStimation and Inference in Structured samples (GENESIS), weighed LME and IWLME provide a more precise estimate of the effect size with smaller bias and mean square error, compared with LME and generalized estimating equations (GEE). In an Epi-genome wide association study, by applying IWLME, more CpGs reach the significance threshold compared with LME. We then explore R2 statistics in LME, defining R2 as the proportion of the variance in the response that is predictable from the fixed effect variables. We review six existing R2 estimators and extend these estimators to estimate partial R2. We propose three R2/partial R2 estimators based on our R2 definition and variance decomposition. We compare the performance among the methods by simulation studies. Our proposed R2 estimators have the smallest mean square error, low bias, and no or only a small percentage of negative estimation when the true R2/partial R2 is modest or higher (>2%). Finally, a Firth bias corrected generalized estimating equations (FBC-GEE) approach is proposed to address separation for correlated binary data, a common occurrence in association analyses of rare genetic variants. We compare GEE, FBC-GEE, Firth logistic regression and Scalable and Accurate Implementation of GEneralized mixed model (SAIGE) by conducting simulation studies. FBC-GEE helps reduce type I error inflation compared with GEE. With these projects, we develop new methodologies and improve the understanding of the performance of available methods for genetics studies with family data. Advisors/Committee Members: Yang, Qiong (advisor).

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Li, S. (2019). Methods for correlated observations with applications to genetic association studies. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/38977

Chicago Manual of Style (16^th Edition):

Li, Shuo. “Methods for correlated observations with applications to genetic association studies.” 2019. Doctoral Dissertation, Boston University. Accessed February 27, 2021. http://hdl.handle.net/2144/38977.

MLA Handbook (7^th Edition):

Li, Shuo. “Methods for correlated observations with applications to genetic association studies.” 2019. Web. 27 Feb 2021.

Vancouver:

Li S. Methods for correlated observations with applications to genetic association studies. [Internet] [Doctoral dissertation]. Boston University; 2019. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2144/38977.

Council of Science Editors:

Li S. Methods for correlated observations with applications to genetic association studies. [Doctoral Dissertation]. Boston University; 2019. Available from: http://hdl.handle.net/2144/38977

University of Iowa

26. Yu, Lixi. Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM.

Degree: PhD, Biostatistics, 2016, University of Iowa

URL: https://ir.uiowa.edu/etd/2301

► Due to the rapid development and growing need for information technologies, more and more researchers start to focus on high-dimensional data. Much work has… (more)

▼ Due to the rapid development and growing need for information technologies, more and more researchers start to focus on high-dimensional data. Much work has been done on problems like point estimation possessing oracle inequalities, coefficient estimation, variable selection in high-dimensional regression models. However, with respect to the statistical inference for the regression coefficients, there have been few studies. Therefore, we propose a regularized efficient score estimation and testing (RESET) approach for treatment effects in the presence of nuisance parameters, either low-dimensional or high-dimensional, in generalized linear models (GLMs). Based on the RESET method, we are also able to develop another two-step approach related to the same problem. The RESET approach is based on estimating the efficient score function of the treatment parameters. This means we are trying to remove the influence of nuisance parameters on the treatment parameters and construct an efficient score function which could be used for estimating and testing for the treatment effect. The RESET approach can be used in both low-dimensional and high-dimensional settings. As the simulation results show, it is comparable with the commonly used maximum likelihood estimators in most low-dimensional cases. We will prove that the RESET estimator is consistent under some regularity conditions, either in the low-dimensional or the high-dimensional linear models. Also, it is shown that the efficient score function of the treatment parameters follows a chi-square distribution, based on which the regularized efficient score tests are constructed to test for the treatment effect, in both low-dimensional and high-dimensional GLMs. The two-step approach is mainly used for high-dimensional inference. It combines the RESET approach with a first step of selecting "promising" variables for the purpose of reducing the dimension of the regression model. The minimax concave penalty is adopted for its oracle property, which means it tends to choose "correct" variables asymptotically. The simulation results show that some improvement is still required for this approach, which will be part of our future research direction. Finally, both the RESET and the two-step approaches are implemented with a real data example to demonstrate their application, followed by a conclusion for all the problems investigated here and a discussion for the directions of future research. Advisors/Committee Members: Huang, Jian (supervisor).

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Yu, L. (2016). Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/2301

Chicago Manual of Style (16^th Edition):

Yu, Lixi. “Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM.” 2016. Doctoral Dissertation, University of Iowa. Accessed February 27, 2021. https://ir.uiowa.edu/etd/2301.

MLA Handbook (7^th Edition):

Yu, Lixi. “Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM.” 2016. Web. 27 Feb 2021.

Vancouver:

Yu L. Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM. [Internet] [Doctoral dissertation]. University of Iowa; 2016. [cited 2021 Feb 27]. Available from: https://ir.uiowa.edu/etd/2301.

Council of Science Editors:

Yu L. Regularized efficient score estimation and testing (reset) approach in low-dimensional and high-dimensional GLM. [Doctoral Dissertation]. University of Iowa; 2016. Available from: https://ir.uiowa.edu/etd/2301

University of Cape Town

27. Van Biljon, Noëlle. Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven.

Degree: MSc, Statistical Sciences, 2020, University of Cape Town

URL: http://hdl.handle.net/11427/32370

► HIV infected (HIV+) children initiate antiretroviral therapy (ART) early in life and remain on it lifelong. However, the long-term impact of ART and HIV on… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Van Biljon, N. (2020). Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven. (Masters Thesis). University of Cape Town. Retrieved from http://hdl.handle.net/11427/32370

Chicago Manual of Style (16^th Edition):

Van Biljon, Noëlle. “Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven.” 2020. Masters Thesis, University of Cape Town. Accessed February 27, 2021. http://hdl.handle.net/11427/32370.

MLA Handbook (7^th Edition):

Van Biljon, Noëlle. “Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven.” 2020. Web. 27 Feb 2021.

Vancouver:

Van Biljon N. Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven. [Internet] [Masters thesis]. University of Cape Town; 2020. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/11427/32370.

Council of Science Editors:

Van Biljon N. Longitudinal analysis of Brain Metabolite levels for HIV infected Children from ages five to eleven. [Masters Thesis]. University of Cape Town; 2020. Available from: http://hdl.handle.net/11427/32370

University of Cape Town

28. Mccready, Carlyle. Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study.

Degree: MSc, Statistical Sciences, 2019, University of Cape Town

URL: http://hdl.handle.net/11427/31822

► This research project analysed data collected with the use of self-reporting questionnaires and observational video scores in order to determine the level of success achieved… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Mccready, C. (2019). Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study. (Masters Thesis). University of Cape Town. Retrieved from http://hdl.handle.net/11427/31822

Chicago Manual of Style (16^th Edition):

Mccready, Carlyle. “Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study.” 2019. Masters Thesis, University of Cape Town. Accessed February 27, 2021. http://hdl.handle.net/11427/31822.

MLA Handbook (7^th Edition):

Mccready, Carlyle. “Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study.” 2019. Web. 27 Feb 2021.

Vancouver:

Mccready C. Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study. [Internet] [Masters thesis]. University of Cape Town; 2019. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/11427/31822.

Council of Science Editors:

Mccready C. Latent Variable Models for Longitudinal Outcomes from a Parenting Intervention Study. [Masters Thesis]. University of Cape Town; 2019. Available from: http://hdl.handle.net/11427/31822

University of Minnesota

29. Hatfield, Laura A. Bayesian hierarchical joint modeling for longitudinal and survival data.

Degree: PhD, Biostatistics, 2011, University of Minnesota

URL: http://purl.umn.edu/115715

► In studying the evolution of a disease and effects of treatment on it, investigators often collect repeated measures of disease severity (longitudinal data) and measure… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Hatfield, L. A. (2011). Bayesian hierarchical joint modeling for longitudinal and survival data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/115715

Chicago Manual of Style (16^th Edition):

Hatfield, Laura A. “Bayesian hierarchical joint modeling for longitudinal and survival data.” 2011. Doctoral Dissertation, University of Minnesota. Accessed February 27, 2021. http://purl.umn.edu/115715.

MLA Handbook (7^th Edition):

Hatfield, Laura A. “Bayesian hierarchical joint modeling for longitudinal and survival data.” 2011. Web. 27 Feb 2021.

Vancouver:

Hatfield LA. Bayesian hierarchical joint modeling for longitudinal and survival data. [Internet] [Doctoral dissertation]. University of Minnesota; 2011. [cited 2021 Feb 27]. Available from: http://purl.umn.edu/115715.

Council of Science Editors:

Hatfield LA. Bayesian hierarchical joint modeling for longitudinal and survival data. [Doctoral Dissertation]. University of Minnesota; 2011. Available from: http://purl.umn.edu/115715

University of Minnesota

30. Kong, Xiaoxiao. Statistical methods in genome sequence analysis.

Degree: PhD, Biostatistics, 2011, University of Minnesota

URL: http://purl.umn.edu/117828

► Mass spectral data alignment study. The first part of this thesis deals with the need to align spectra to correct for massto- charge experimental variation… (more)

▼ Mass spectral data alignment study. The first part of this thesis deals with the need to align spectra to correct for massto- charge experimental variation in clinical applications of mass spectrometry (MS). Proteomics is the large-scale study of proteins. The term “proteomics” was first coined in 1997 to make an analogy with genomics, the study of genes. Most MS-based proteomic data analysis methods involve a two-step approach, identify peaks first and then do the alignment and statistical inference on these identified peaks only. However, the peak identification step relies on prior information on the proteins of interest or a peak detection model, both of which are subject to error. Also numerous additional features such as peak shape and peak width are lost in simple peak detection, and these are informative for correcting mass variation in the alignment step. Here we present a novel Bayesian approach to align the complete spectra. The approach is based on a parametric model which assumes the spectrum and alignment function are Gaussian processes, but the alignment function is monotone. We show how to use the expectation-maximization algorithm to find the posterior mode of the set of alignment functions and the mean spectrum for a patient population. After alignment, we conduct tests while controlling for error attributable to multiple comparisons on the level of the peaks identified from the absolute mean spectra difference of two patient populations. Motif discovery study. In the second part of this thesis we show how to reformulate the usual model-based approach to motif detection as a conditional log-linear model and how this reformulation of the problem allows one to use the lasso to build complex dependency structures into the motif probability model in a fashion that is not overparameterized. We illustrate the performance of the approach with a set of simulations and show that it can dramatically outperform existing methods when there is dependence in the motif and is comparable in cases where there is no dependence. By not marginalizing out the parameters that govern the probability distribution of the motif (as is usually done), we can characterize the motif in a more rigorous fashion. In the final part of the thesis we describe how to incorporate the Bayesian group lasso, the Bayesian adaptive lasso, and the Bayesian group adaptive lasso into conditional loglinear modeling for motif discovery. If an explanatory factor is represented by a group of derived input variables, the lasso tends to select individual derived input variables from the grouped variables, while the group lasso could overcome this difficulty and still do variable selection at the group level. Also the lasso shrinkage produces biased estimates for the large coefficients, while the adaptive group lasso can overcome this difficulty and maintain the oracle property. Finally the group adaptive lasso enjoys both the advantage of the group lasso and the adaptive lasso.

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Kong, X. (2011). Statistical methods in genome sequence analysis. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/117828

Chicago Manual of Style (16^th Edition):

Kong, Xiaoxiao. “Statistical methods in genome sequence analysis.” 2011. Doctoral Dissertation, University of Minnesota. Accessed February 27, 2021. http://purl.umn.edu/117828.

MLA Handbook (7^th Edition):

Kong, Xiaoxiao. “Statistical methods in genome sequence analysis.” 2011. Web. 27 Feb 2021.

Vancouver:

Kong X. Statistical methods in genome sequence analysis. [Internet] [Doctoral dissertation]. University of Minnesota; 2011. [cited 2021 Feb 27]. Available from: http://purl.umn.edu/117828.

Council of Science Editors:

Kong X. Statistical methods in genome sequence analysis. [Doctoral Dissertation]. University of Minnesota; 2011. Available from: http://purl.umn.edu/117828

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Open Access Theses and Dissertations