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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 ·
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CSE |
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to Zotero / EndNote / Reference
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APA (6th 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 (16th 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 (7th 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)
▼ 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 method used to find the thresholds for the shrinkage Bayesian estimation ofquantitative trait loci parameters and three algorithms of handling the missing genotypeproblems in multiple QTL mapping under the generalized linear mixed model framework.In addition, this dissertation includes a review on Bayesian statistics and somedata analyses using Markov chain Monte Carlo (MCMC). Chapter 2 is a review of the Bayesian statistics and some data analyses usingMCMC. It includes almost all the aspects of Bayesian statistics such as Bayes' theorem, prior and posterior distributions, Bayesian inference, and Markov chain Monte Carlo (MCMC) algorithms. In Chapter 3, a new way to conduct the permutation test under the Shrinkage Bayesian method is developed. Permutation test is the most frequently used method for statistical test for QTL mapping. And it was applied on the QTL mapping based on the Bayesian approach. While using the traditional permutation test to get the thresholds for QTL mapping from the MCMC algorithms in the Bayesian models isquite time-consuming, a new way to permute the samples from the MCMC algorithmsis performed in Chapter 3. Empirical power analysis is done to test the method through the simulations. Generalized linear mixed model has been applied to analyze the discrete traits. Research on handling the missing genotype problems in multiple QTL mapping under the generalized linear mixed model framework is presented in Chapter 4. Three algorithms were proposed: (1) expectation algorithm, (2) overdispersion model algorithm and (3)mixture model algorithm.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 (6th 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 (16th 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 (7th 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 (6th 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 (16th 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 (7th 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)
▼ 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 on outcomes, in the presence of unobserved confounders and/or measurement errors in covariates. Consistent estimation of the effect has been developed when the outcome is continuous, while methods for binary outcome produce inconsistent estimation. In this dissertation, we examine two IV methods in the literature for binary outcome and show the bias in parameter estimate by a simulation study. The identifiability problem of IV analysis with binary outcome is discussed. Moreover, IV methods for time-to-event outcome with censored data remain underdeveloped. We propose two Bayesian approaches for IV analysis with censored time-to-event outcome by using a two-stage linear model: One is a parametric Bayesian model with normal and non-normal elliptically contoured error distributions, and the other is a semiparametric Bayesian model with Dirichlet process mixtures for the random errors, in order to relax the parametric assumptions and address heterogeneous clustering problems. Markov Chain Monte Carlo sampling methods are developed for both parametric and semiparametric Bayesian models to estimate the endogenous parameter. Performance of our methods is examined by simulation studies. Both methods largely reduce bias in estimation and greatly improve coverage probability of the endogenous parameter, compared to the regular method where the unobserved confounders and/or measurement errors are ignored. We illustrate our methods on the Women's Health Initiative Observational Study and the Atherosclerosis Risk in Communities Study.
Subjects/Keywords: Biostatistics
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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 (6th 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 (16th 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 (7th 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)
▼ 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 intraclass correlations coefficients (ICCs) in the two arms. The efficacy of the intervention may be measured in terms of the risk difference (RD), relative risk (RR) or odds ratio (OR). We define cost efficiency (CE) as the ratio of the precision of the efficacy measure to the study cost and develop optimal allocations to the two arms for maximizing CE. The optimal design, which is based on the optimal allocation, could be different for different measures. We define relative cost efficiency (RCE) of a design as the ratio of its CE to CE of the optimal design and use RCE to compare different designs. Because the optimal allocation can be highly sensitive to the unknown ICCs and anticipated success rates, we propose a Bayesian method and a maximin method to construct an efficient and robust design. We show that the RCE of the designs based on the Bayesian method or the maximin method is generally larger than the balanced design. Based on the optimal allocation, we derive optimal sample size formulas which satisfy the power requirement and minimize the total study cost. All the results above are based on the assumption of constant cluster size. When there is extreme variation in cluster size, the usually used sample size formula assuming a constant cluster size may result in a design with low power. Assuming a balanced design, we develop a sample size formula for a two-arm CRT which obtains the desired power even though the cluster sizes are very different. This formula can be modified to incorporate optimal allocation consideration, hence it minimizes the study cost while satisfying the power requirement for a CRT with varying cluster sizes. Simulation is used to verify that our formulas can obtain the desired power.
Subjects/Keywords: Biostatistics
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APA ·
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APA (6th 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 (16th 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 (7th 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)
▼ 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 built on the theory of cross-validation and allows for a general class of algorithms to be considered for the ensemble. The oracle results for the cross-validation selector are extended to the super learner. Due to the established oracle results for the cross-validation selector, the super learner is proven to represent an asymptotically optimal framework for learning. We discuss the super learner algorithm and demonstrate the method on a series of data analysis problems. The super learner framework is extended to cover censored data by applying an appropriate observed data loss function. The final chapter presents an R package for implementing the super learner based on a general library of learners.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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)
▼ 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. Chapter 1 describes the relaxnet package, which extends the glmnet package with relaxation (as in the relaxed lasso of Meinshausen, 2007). Chapter 2 describes the widenet package, which extends relaxnet with polynomial basis expansions. Chapter 3 describes the multiPIM package, which takes a causal inference approach to variable importance analysis. Section 3.7 describes an analysis of data from the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study (Rahbar et al., 2012; Hubbard et al., 2013), for which the multiPIM package is used in conjunction with the relaxnet and widenet packages to estimate variable importances.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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)
▼ 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 maternal morbidity. Methods: Medical records of women with severe hypertension (at least two severe blood pressures, systolic ≥160mmHg and/or diastolic ≥110mmHg, within 60 minutes) were accessed for timing of severe blood pressures, timing of treatment, and blood pressure response to treatment. Severe maternal morbidity was confirmed by multidisciplinary case review. We compared the incidence of severe maternal morbidity between women who received timely (within 60 minutes of diagnosis) vs. not-timely treatment. Results: Of 465 women with severe hypertension, 29 (6.2%) experienced severe maternal morbidity. Fifty-six percent of women received timely treatment, of whom 1.9% had severe maternal morbidity, compared with 6.4% of women who did not receive timely treatment (p=0.02). Timely treatment was associated with a 72% reduction in relative odds of severe maternal morbidity (p=0.02). No significant difference was seen in median pre-treatment systolic pressures (p=0.20) between the groups. Conclusion: Antihypertensive treatment within 60 minutes of confirmed diagnosis of severe hypertension was associated with reduction in severe maternal morbidity. Our findings support current recommendations to treat all women with severe hypertension with antihypertensive medications in a timely fashion.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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)
▼ The log rank test is a popular nonparametric test for comparing the marginal survival distribution of two groups. When data are organized within clusters and the size of clusters or the distribution of group membership within a cluster is related to an outcome of interest, traditional methods of data analysis can be biased. In this thesis, we develop a within-cluster group weighted log rank test to compare marginal survival time distributions between groups from clustered data, correcting for cluster size and intra-cluster group size informativeness. The performance of this new test is compared with the unweighted and cluster-weighted log rank tests via a simulation study. The simulation results suggest the new test performs appropriately under scenarios of cluster size and intra-cluster group size informativeness, and produces higher power than the two comparison tests under non-informative scenarios. The new test is then illustrated on a live data set comparing time to functional improvement in task performance from patients with spinal cord injuries.
Advisors/Committee Members: Lorenz, Douglas, Datta, Somnath, Datta, Somnath, Terson de Paleville, Daniela.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 (6th 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 (16th 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 (7th 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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MLA ·
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APA (6th 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 (16th 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 (7th 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)
▼ 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 has been performed the study administrators have additional information about the treatments, which is withheld from new recruits. For true informed consent, this information should be given to new study recruits to use in making a personal decision about their desired treatment. We present a method (and the rationale behind the method) that provides unbiased estimates of hazard ratios when new recruits are given information from interim analyses and allowed to choose their own treatments. We then developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem evolving), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Finally, using novel statistical models, we investigated the impact of POPs (in particular, non-dioxin-like polychlorinated biphenyl, IUPAC no.: 153; ”PCB153”) on human health through the disruption of natural gut microbiota establishment in infants. We created novel distributed lag two-part models to account for the cumulative exposure of POPs.
Advisors/Committee Members: Pagano, Marcello (advisor), Hide, Winston (committee member), Dominici, Francesca (committee member).
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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)
▼ 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 adjustment for measurement error in time to event data. Measurement error in time to event data used as a predictor will lead to inaccurate predictions. This arises in the context of self-reported family history, a time to event covariate often measured with error, used in Mendelian risk prediction models. Using validation data, we propose a method to adjust for measurement error in this setting. We estimate the measurement error process using a nonparametric smoothed Kaplan-Meier estimator, and use Monte Carlo integration to implement the adjustment. We apply our method to simulated data in the context of Mendelian risk prediction models and multivariate survival prediction models, and illustrate our method using a data application for Mendelian risk prediction models. Results show our adjusted method corrects for measurement error mainly in two aspects; by improving calibration and total accuracy. In some scenarios discrimination is also improved. In chapter two, we use the methods proposed in chapter one to extend Mendelian risk prediction models to handle misreported family history.
Advisors/Committee Members: Parmigiani, Giovanni (advisor), Spiegelman, Donna (committee member), Cai, Tianxi (committee member), Gorfine, Malka (committee member).
Subjects/Keywords: Biostatistics
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
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APA (6th 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 (16th 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 (7th 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)
▼ The visual world paradigm is a tool that is widely used in the field of psycholinguistics to help investigate how people listen and understand words and sentences. Proportions of fixations to several different objects are recorded for a number of subjects, over a specific time period. Researchers have found it difficult to find models that can incorporate multiple random effects, account for the correlated nature of the data, and simultaneously fit multiple fixation curves/groups. We have taken a Bayesian hierarchical modeling approach for this multivariate non-linear longitudinal data. Within in this framework, we look at both parametric and nonparametric approaches in simultaneously modeling multiple curves. Finally, we will look at different comparison techniques to compare these curves under a Bayesian framework.
Advisors/Committee Members: Oleson, Jacob J. (supervisor).
Subjects/Keywords: Biostatistics
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APA ·
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MLA ·
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CSE |
Export
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APA (6th 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 (16th 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 (7th 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)
▼ 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 (GWAS). Kernel-based variance component methods such as SKAT are flexible and computationally efficient methods for identifying marginal associations. A kernel-based variance component method, called the Gene-centric Gene-Gene Interaction with Smoothing-sPline ANOVA model (SPA3G) was proposed to identify gene-gene interactions for a quantitative trait. For interaction testing, the SPA3G method performs better than some SNP-based approaches under many scenarios.
In this thesis, we evaluate the properties of the SPA3G method and extend SPA3G using alternative p-value approximations and interaction kernels. This thesis focuses on common variants only. Our simulation results show that the allele matching interaction kernel, combined with the method of moments p-value approximation, leads to inflated type I error in small samples. For small samples, we propose a Principal Component (PC)-based interaction kernel and computing p-values with a 3-moment adjustment that yield more appropriate type I error. We also propose a weighted PC kernel that has higher power than competing approaches when interaction effects are sparse. By combining the two proposed kernels, we develop omnibus methods that obtain near-optimal power in most settings. Finally, we illustrate how to analyze the interaction between selected gene pairs on the age at natural menopause (ANM) from the Framingham Heart Study.
Subjects/Keywords: Biostatistics
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 (6th 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 (16th 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 (7th 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)
▼ 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 the maturing brain is not well documented and longitudinal neuroimaging studies are rare, especially in developing countries most heavily impacted by HIV/AIDS where access to imaging resources are limited. We have examined HIV related changes in metabolite level trajectories from 5-11 years in three brain regions using Magnetic Resonance Spectroscopy (MRS). We used univariate linear mixed effect models to identify independent profiles of the metabolites measured in each region of the brain. To explore the metabolite trends in a multivariate setting we generated multilevel mixed effects models, and correlated response models. There was an element of confounding introduced through the change of MRI scanner during the follow-up period and we compare different methods to resolve this issue. Consequently, we did observe differences in metabolite profiles from HIV+ children compared to HIV uninfected (HIV-) controls. This suggests that while these children are on ART treatment, there is still some underlying effect on their neurochemistry which sets their development apart from the normal healthy profiles we expect.
Advisors/Committee Members: Little, Francesca (advisor), Meintjes, Ernesta (advisor), Holmes, Martha (advisor), Robertson, Frances (advisor).
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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)
▼ 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 by the Sinovuyo Caring Families Programme (SCFP). The SCFP aimed to reduce harsh parenting practices and child behavioural problems in high-risk South African families. This research project examined the use of structural equation modelling (SEM) for longitudinal profiles and latent growth mediation modelling. Improved behaviour was observed in terms of reported child behaviour problems and reported harsh parenting with differences between the intervention and control groups directly after the completion of the 3-month intervention program. Improved behaviour was also observed in terms of reported positive parenting with differences between the intervention and control groups directly after the completion of the 3- month intervention program and at the 12-month follow-up occasion. No improvement in observed child behaviour was mediated through reported positive parenting or reported harsh parenting. Furthermore, the intervention program led to improved positive parenting behaviour directly after the 3-month intervention period, however the improved behaviour of the parent did not act as a mediating variable and no improvement in child behaviour was observed as a result.
Advisors/Committee Members: Little, Francesca (advisor).
Subjects/Keywords: Biostatistics
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
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APA (6th 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 (16th 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 (7th 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)
▼ 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 time to
occurrence of a clinical event (survival data). The development of joint models for such
longitudinal and survival data often uses individual-specific latent processes that evolve
over time and contribute to both the longitudinal and survival outcomes. Such models
allow substantial flexibility to incorporate association across repeated measurements,
among multiple longitudinal outcomes, and between longitudinal and survival outcomes.
The joint modeling framework has been extended to handle many complexities of
real data, but less attention has been paid to the properties of such models. We are
interested in the “payoff” of joint modeling, that is, whether using two sources of data
simultaneously offers better inference on individual- and population-level characteristics,
as compared to using them separately. We consider the problem of attributing
informational content to the data inputs of joint models by developing analytical and
numerical approaches and demonstrating their use.
As a motivating application, we consider a clinical trial for treatment of mesothelioma,
a rapidly fatal form of lung cancer. The trial protocol included patient-reported
outcome (PRO) collection throughout the treatment phase and followed patients until
progression or death to determine progression-free survival times. We develop models
that extend the joint modeling framework to accommodate several features of the longitudinal
data, including bounded support, excessive zeros, and multiple PROs measured
simultaneously. Our approaches produce clinically relevant treatment effect estimates
on several aspects of disease simultaneously and yield insights on individual-level variation
in disease processes.
Subjects/Keywords: Biostatistics
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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 ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th 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 (16th 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 (7th 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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