subject:(biostatistics)

University of Cincinnati

1. Wang, Qin. Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective.

Degree: MS, Medicine: Biostatistics (Environmental Health), 2015, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428070351

► There are about 5000 hospitals in the United States. The Health Care Cost and Utilization Project (HCUP) has been collecting data on admissions to hospitals… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Wang, Q. (2015). Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428070351

Chicago Manual of Style (16^th Edition):

Wang, Qin. “Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective.” 2015. Masters Thesis, University of Cincinnati. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428070351.

MLA Handbook (7^th Edition):

Wang, Qin. “Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective.” 2015. Web. 23 Sep 2019.

Vancouver:

Wang Q. Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428070351.

Council of Science Editors:

Wang Q. Short Term Trend Analysis of Hospital Admissions Due to Red Blood Cell Disorders: Big Data Perspective. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1428070351

The Ohio State University

2. Ding, Jie. Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure.

Degree: PhD, Biostatistics, 2008, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1218475579

► Family-based association test is one way of mapping disease susceptibility genes by testing for association between marker genotypes and disease phenotypes in family data. Missing… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Ding, J. (2008). Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1218475579

Chicago Manual of Style (16^th Edition):

Ding, Jie. “Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure.” 2008. Doctoral Dissertation, The Ohio State University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1218475579.

MLA Handbook (7^th Edition):

Ding, Jie. “Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure.” 2008. Web. 23 Sep 2019.

Vancouver:

Ding J. Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure. [Internet] [Doctoral dissertation]. The Ohio State University; 2008. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1218475579.

Council of Science Editors:

Ding J. Monte Carlo Pedigree Disequilibrium Test with Missing Data and Population Structure. [Doctoral Dissertation]. The Ohio State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1218475579

The Ohio State University

3. Yang, Jingyuan. Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies.

Degree: PhD, Biostatistics, 2010, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275426657

► Genomic imprinting and maternal effect are involved in many complex human diseases but have long been neglected in association studies. In this dissertation, we… (more)

▼ Genomic imprinting and maternal effect are involved in many complex human diseases but have long been neglected in association studies. In this dissertation, we propose two likelihood approaches for detecting imprinting and maternal effects (LIME) simultaneously in family-based association studies. Since these two effects could cause similar parent-of-origin patterns in binary disease traits, it is important to incorporate both of them into the modeling to avoid lurking effects. Statistical methods that are developed to detect one of them while assuming the absence of the other will report false positives when the assumption is violated. Our first LIME approach (LIME-ped) is designed for general pedigrees with missing genotypes from prospective family-based association studies. LIME-ped formulates the probability of familial genotypes by introducing a novel concept called "conditional mating type" between marry-in founders and their non-founder spouses, and models the penetrance using a logit link. To deal with missing genotypes, LIME-ped enumerates possible unobserved genotypes and sums over the likelihoods of all compatible familial genotypes conditional on observed genotypes. Our simulation study demonstrates that: (1) LIME-ped has the correct type I error rate for testing for imprinting when maternal effect is present, or vice versa; (2) applying LIME-ped to pedigrees fully utilizes the data and achieves higher power than trimming down the pedigrees to nuclear families; (3) "filling in" the unobserved genotypes conditional on the genotypes of relatives augments the total information, leading to higher power for LIME-ped than simply excluding individuals with missing genotypes. The second LIME approach (LIME-mix) is designed for case-parent/control-parent triads studies. Since biological fathers are often hard to recruit in family-based studies, we also allow for case-mother/control-mother pairs arising from the triads with missing fathers. The approach is referred to as "LIME-mix", since the real data is a mixed sample of triads and pairs. We assume multiplicative relative risks due to variant allele effect, genomic imprinting, and maternal effect; and analytically derive the partial likelihood of the family counts with particular genotype combinations. LIME-mix can be applied to either rare or common diseases without restriction on the disease prevalence. Since the partial likelihood does not involve any nuisance parameters about mating types, LIME-mix makes no assumptions on the mating type frequencies, such as allelic exchangeability and mating symmetry, the latter of which is a necessary assumption universally made in many existing imprinting and/or maternal effects detection methods. The robustness of the proposed LIME-mix approach compared to two existing methods is demonstrated via simulation. The LIME approaches are applied to nuclear families, general pedigrees and case-control families from the Framingham Heart Study data. Several SNPs that have variant allele, imprinting and/or… Advisors/Committee Members: Lin, Shili (Advisor).

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Yang, J. (2010). Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1275426657

Chicago Manual of Style (16^th Edition):

Yang, Jingyuan. “Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies.” 2010. Doctoral Dissertation, The Ohio State University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275426657.

MLA Handbook (7^th Edition):

Yang, Jingyuan. “Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies.” 2010. Web. 23 Sep 2019.

Vancouver:

Yang J. Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies. [Internet] [Doctoral dissertation]. The Ohio State University; 2010. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275426657.

Council of Science Editors:

Yang J. Likelihood Approaches for Detecting Imprinting and Maternal Effects in Family-Based Association Studies. [Doctoral Dissertation]. The Ohio State University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275426657

The Ohio State University

4. Hinton, Alice M. Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications.

Degree: PhD, Biostatistics, 2014, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1390479004

► There are a variety of methods available to classify an object into one of two populations. Here, the method of discriminant analysis is considered in… (more)

▼ There are a variety of methods available to classify an object into one of two populations. Here, the method of discriminant analysis is considered in the cross-sectional and the longitudinal setting with a structured multivariate normal model. The generalized likelihood ratio change detection algorithm is also investigated as an alternative to methods based on discriminant analysis in the longitudinal setting.Traditionally, discriminant functions are developed to classify a new observation from a cross-sectional dataset into a population. An error is made when the observation is incorrectly classified. In the literature, several parametric and empirical methods of estimating these misclassification probabilities have been proposed. The performance of six parametric and three empirical misclassification probability estimators are compared. It is found that the parametric methods, which rely on an assumption of normality, generally outperform the empirical methods when a linear discriminant function is used for classification and the data originate from normal populations. The preferred parametric method depends on the size of the training dataset and the parameters of the populations, particularly the distance between the means. The empirical methods are preferred only when the two populations are well separated and the variances are significantly different.The ideas of discriminant analysis are used to develop a classifier for a multivariate longitudinal dataset in which a change in both mean and variance occurs at an unknown time. Conditional distributions involving a patterned covariance matrix accounting for the correlations between the variables as well as the correlations present across time are then utilized to develop a discriminant function. After a training dataset is used to provide estimates for each of the parameters needed to specify the discriminant function, the classifier can be sequentially applied as observations are accumulated to identify the time at which the change occurs. The generalized likelihood ratio change detection algorithm is an alternative to the classifier based on the discriminant function. The algorithm assumes a known direction but unknown magnitude of change in the mean and no change in the variance. The probability of the algorithm detecting a change at a time greater than a specified time point is theoretically derived and approximated using simulation. The robustness of the algorithm to correlation in the data is also investigated and it is found to be robust only to small longitudinal correlations.Both the method based on the discriminant function as well as the generalized likelihood ratio change detection algorithm are applied to a multivariate longitudinal dataset composed of patients with lupus nephritis. The method based on the discriminant function uses the data as a training dataset resulting in a classifier which can be used to monitor a new lupus patient for renal inflammation. The generalized likelihood ratio change detection algorithm provides an alternative method… Advisors/Committee Members: Nagaraja, Haikady (Advisor).

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Hinton, A. M. (2014). Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1390479004

Chicago Manual of Style (16^th Edition):

Hinton, Alice M. “Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications.” 2014. Doctoral Dissertation, The Ohio State University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1390479004.

MLA Handbook (7^th Edition):

Hinton, Alice M. “Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications.” 2014. Web. 23 Sep 2019.

Vancouver:

Hinton AM. Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications. [Internet] [Doctoral dissertation]. The Ohio State University; 2014. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1390479004.

Council of Science Editors:

Hinton AM. Contributions to Discriminant Analysis of Cross-Sectional and Longitudinal Data with Applications. [Doctoral Dissertation]. The Ohio State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1390479004

Case Western Reserve University

5. HAN, XIAOZHEN. Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach.

Degree: MSs, Epidemiology and Biostatistics, 2015, Case Western Reserve University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1427993855

► The association of bivariate failure times, estimated using Spearman’s correlation coefficient (Spearman’s r_s) herein, is of great interest in biology and medicine. Our objectives are… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

HAN, X. (2015). Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach. (Masters Thesis). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1427993855

Chicago Manual of Style (16^th Edition):

HAN, XIAOZHEN. “Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach.” 2015. Masters Thesis, Case Western Reserve University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1427993855.

MLA Handbook (7^th Edition):

HAN, XIAOZHEN. “Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach.” 2015. Web. 23 Sep 2019.

Vancouver:

HAN X. Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach. [Internet] [Masters thesis]. Case Western Reserve University; 2015. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1427993855.

Council of Science Editors:

HAN X. Evaluating the Correlation Coefficient of Bivariate Failure Times: A Copula-based Approach. [Masters Thesis]. Case Western Reserve University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1427993855

University of California, Berkeley

6. 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 (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Thesis, University of California, Berkeley. Accessed September 23, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10150887.

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

MLA Handbook (7^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Web. 23 Sep 2019.

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 2019 Sep 23]. 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

UCLA

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

Degree: Clinical Research, 2017, UCLA

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Gupta, Megha. “Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity.” 2017. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/37p7m7v0.

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

MLA Handbook (7^th Edition):

Gupta, Megha. “Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity.” 2017. Web. 23 Sep 2019.

Vancouver:

Gupta M. Timely Treatment of Severe Maternal Hypertension and Reduction in Severe Maternal Morbidity. [Internet] [Thesis]. UCLA; 2017. [cited 2019 Sep 23]. 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

8. Abdia, Younathan. Propensity score based methods for estimating the treatment effects based on observational studies.

Degree: PhD, 2016, University of Louisville

URL: 10.18297/etd/2504 ; https://ir.library.louisville.edu/etd/2504

► This dissertation consists of two interconnected research projects. The first project was a study of propensity scores based statistical methods for estimating the average… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Abdia, Y. (2016). Propensity score based methods for estimating the treatment effects based on observational studies. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/2504 ; https://ir.library.louisville.edu/etd/2504

Chicago Manual of Style (16^th Edition):

Abdia, Younathan. “Propensity score based methods for estimating the treatment effects based on observational studies.” 2016. Doctoral Dissertation, University of Louisville. Accessed September 23, 2019. 10.18297/etd/2504 ; https://ir.library.louisville.edu/etd/2504.

MLA Handbook (7^th Edition):

Abdia, Younathan. “Propensity score based methods for estimating the treatment effects based on observational studies.” 2016. Web. 23 Sep 2019.

Vancouver:

Abdia Y. Propensity score based methods for estimating the treatment effects based on observational studies. [Internet] [Doctoral dissertation]. University of Louisville; 2016. [cited 2019 Sep 23]. Available from: 10.18297/etd/2504 ; https://ir.library.louisville.edu/etd/2504.

Council of Science Editors:

Abdia Y. Propensity score based methods for estimating the treatment effects based on observational studies. [Doctoral Dissertation]. University of Louisville; 2016. Available from: 10.18297/etd/2504 ; https://ir.library.louisville.edu/etd/2504

University of Louisville

9. Wan, Yubing. Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data.

Degree: PhD, 2014, University of Louisville

URL: 10.18297/etd/1508 ; https://ir.library.louisville.edu/etd/1508

► The focus of this dissertation is to develop statistical methods, under the framework of penalized regressions, to handle three different problems. The first research… (more)

▼ The focus of this dissertation is to develop statistical methods, under the framework of penalized regressions, to handle three different problems. The first research topic is to address missing data problem for variable selection models including elastic net (ENet) method and sparse partial least squares (SPLS). I proposed a multiple imputation (MI) based weighted ENet (MI-WENet) method based on the stacked MI data and a weighting scheme for each observation. Numerical simulations were implemented to examine the performance of the MIWENet method, and compare it with competing alternatives. I then applied the MI-WENet method to examine the predictors for the endothelial function characterized by median effective dose and maximum effect in an ex-vivo experiment. The second topic is to develop monotonic single-index models for assessing drug interactions. In single-index models, the link function f is unnecessary monotonic. However, in combination drug studies, it is desired to have a monotonic link function f . I proposed to estimate f by using penalized splines with I-spline basis. An algorithm for estimating f and the parameter a in the index was developed. Simulation studies were conducted to examine the performance of the proposed models in term of accuracy in estimating f and a. Moreover, I applied the proposed method to examine the drug interaction of two drugs in a real case study. The third topic was focused on the SPLS and ENet based accelerated failure time (AFT) models for predicting patient survival time with mass spectrometry (MS) data. A typical MS data set contains limited number of spectra, while each spectrum contains tens of thousands of intensity measurements representing an unknown number of peptide peaks as the key features of interest. Due to the high dimension and high correlations among features, traditional linear regression modeling is not applicable. Semi-parametric AFT model with an unspecified error distribution is a well-accepted approach in survival analysis. To reduce the bias caused in denoising step, we proposed a nonparametric imputation approach based on Kaplan-Meier estimator. Numerical simulations and a real case study were conducted under the proposed method. Advisors/Committee Members: Kong, Maiying, Datta, Susmita, Datta, Susmita, Kulasekera, Karunarathna, Wu, Dongfeng, Jones, Stephen P..

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Wan, Y. (2014). Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/1508 ; https://ir.library.louisville.edu/etd/1508

Chicago Manual of Style (16^th Edition):

Wan, Yubing. “Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data.” 2014. Doctoral Dissertation, University of Louisville. Accessed September 23, 2019. 10.18297/etd/1508 ; https://ir.library.louisville.edu/etd/1508.

MLA Handbook (7^th Edition):

Wan, Yubing. “Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data.” 2014. Web. 23 Sep 2019.

Vancouver:

Wan Y. Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data. [Internet] [Doctoral dissertation]. University of Louisville; 2014. [cited 2019 Sep 23]. Available from: 10.18297/etd/1508 ; https://ir.library.louisville.edu/etd/1508.

Council of Science Editors:

Wan Y. Penalized regressions for variable selection model, single index model and an analysis of mass spectrometry data. [Doctoral Dissertation]. University of Louisville; 2014. Available from: 10.18297/etd/1508 ; https://ir.library.louisville.edu/etd/1508

Case Western Reserve University

10. Hanook, Sharoon. Analysis of Removable Interaction.

Degree: PhD, Epidemiology and Biostatistics, 2014, Case Western Reserve University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250

► Researchers have always aspired to estimate the most useful and parsimonious model, which helps to obtain the most precise and efficient estimates. Once we have… (more)

▼ Researchers have always aspired to estimate the most useful and parsimonious model, which helps to obtain the most precise and efficient estimates. Once we have a large number of rows and columns in a factorial design, we have many parameters; so the question that arises is: can we obtain better estimates of the parameters of interest by modeling, or by transformation, or by both? In the presence of non-additivity in the model, Interpretation of the model is not very straightforward and it is not easy to describe the model in a most meaningful manner. The scale of measurement can cause interaction and it can be efficiently detected by using any auxiliary information in terms of weights (if at all available) regarding the row and column factor levels. We propose a test that uses available appropriate weights for Tukey’s one degree of freedom test known as weighted Tukey’s test for removable interaction to isolate removable interaction effect from the essential interaction effect. This test uses row and column level weights to effectively detect removable interaction effects in the presence of negligible essential interaction effect. We also proposed a modification of the weighted Tukey’s test due to Rasch et al (2009), using non-linear regression and testing overall model against the sub-model (i.e. no interaction model) by a likelihood ratio test, and showed with simulation that proposed modification is better than Tukey’s, weighted Tukey’s and un-weighted modified Tukey’s test. Better estimates can also be obtained by a transformation, in this dissertation we are proposing an empirical monotonic transformation motivated by Fisher (1950) to remove non-additivity from a two-way analysis of variance model, given the condition that in the presence of negligible essential interaction, there exists some non-additivity in the model that is either completely or partially removable. This transformation provides satisfactory results in the case of different interaction structure types by eliminating removable interaction and making the model more parsimonious. Advisors/Committee Members: Elston, Robert (Committee Chair).

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Hanook, S. (2014). Analysis of Removable Interaction. (Doctoral Dissertation). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250

Chicago Manual of Style (16^th Edition):

Hanook, Sharoon. “Analysis of Removable Interaction.” 2014. Doctoral Dissertation, Case Western Reserve University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250.

MLA Handbook (7^th Edition):

Hanook, Sharoon. “Analysis of Removable Interaction.” 2014. Web. 23 Sep 2019.

Vancouver:

Hanook S. Analysis of Removable Interaction. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2014. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250.

Council of Science Editors:

Hanook S. Analysis of Removable Interaction. [Doctoral Dissertation]. Case Western Reserve University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250

Case Western Reserve University

11. zhang, lu. THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE.

Degree: PhD, Epidemiology and Biostatistics, 2015, Case Western Reserve University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1413540577

► Multiple inferences are widely used in genome-wide association studies, but there are problems existing in family wise error control (FWER). Benjamini & Hochberg (1995) introduced… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

zhang, l. (2015). THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE. (Doctoral Dissertation). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1413540577

Chicago Manual of Style (16^th Edition):

zhang, lu. “THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE.” 2015. Doctoral Dissertation, Case Western Reserve University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1413540577.

MLA Handbook (7^th Edition):

zhang, lu. “THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE.” 2015. Web. 23 Sep 2019.

Vancouver:

zhang l. THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2015. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1413540577.

Council of Science Editors:

zhang l. THE PROBABILITY OF SNPS ASSOCIATED WITH A DISEASE. [Doctoral Dissertation]. Case Western Reserve University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1413540577

Case Western Reserve University

12. Won, Sungho. Improving Genetic Analysis of Case-Control Studies.

Degree: PhD, Epidemiology and Biostatistics, 2008, Case Western Reserve University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1212774902

► The improvement of genotyping technology makes genetic association analysis feasible at the genome-wide level. However, the computational burden for multi-locus analysis is still hard to… (more)

▼ The improvement of genotyping technology makes genetic association analysis feasible at the genome-wide level. However, the computational burden for multi-locus analysis is still hard to handle and often only single SNP analysis with the Cochran-Armitage test is used. For testing association, the possible evidence comprises three typesof information: differences between cases and controls in allele frequencies, in parameters for Hardy Weinberg disequilibrium (HWD) and in parameters for linkagedisequilibrium (LD) of markers. Also, several SNPs near the causal gene may be associated with disease. Thus, an approach that is computationally efficient and uses allpossible information is necessary for inference of association.Biologically, we expect that, at the causal loci, affected individuals are more related evolutionarily than a random pair of individuals from the population and it is known that LD between marker and disease alleles is generally inversely proportional to the distance between them. However, real data show that there can be non-informative markers even near the causal SNP, which indicates that multi-locus analyses based on haplotypes should be considered for locus estimation.Here, first we propose the optimal method for combining p-values using numerical integration or a Monte-Carlo algorithm. The proposed method is always mostpowerful under certain specified conditions and this is confirmed by simulation. With this method, we propose combining either the p-values from three types of information in a single SNP or the p-values from the Cochran Armitage tests of two consecutive SNP markers. Our simulation and application to the Wellcome Trust data show that the proposed method improves statistical power. For locus estimation, while the coalescentbased approach is biologically reasonable but requires a large number of parameters to be estimated, the clustering-based approach is computationally efficient but biologically less reasonable. Thus we propose for fine-scale mapping a haplotype-based clustering algorithm that is constructed through a Bayesian partition model with a generalized similarity measure, and then extend this method to handle phase-unknown haplotypes.Our simulations show that the accuracy of the estimated location of a causal SNP can be improved by using our new algorithm. Advisors/Committee Members: Elston, Robert (Committee Chair), Luo, Yuqun (Committee Co-Chair).

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

Won, S. (2008). Improving Genetic Analysis of Case-Control Studies. (Doctoral Dissertation). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1212774902

Chicago Manual of Style (16^th Edition):

Won, Sungho. “Improving Genetic Analysis of Case-Control Studies.” 2008. Doctoral Dissertation, Case Western Reserve University. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1212774902.

MLA Handbook (7^th Edition):

Won, Sungho. “Improving Genetic Analysis of Case-Control Studies.” 2008. Web. 23 Sep 2019.

Vancouver:

Won S. Improving Genetic Analysis of Case-Control Studies. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2008. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1212774902.

Council of Science Editors:

Won S. Improving Genetic Analysis of Case-Control Studies. [Doctoral Dissertation]. Case Western Reserve University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1212774902

University of California – Riverside

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

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

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Che, Xiaohong. “Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.” 2011. Thesis, University of California – Riverside. Accessed September 23, 2019. http://www.escholarship.org/uc/item/6j96r6pw.

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

MLA Handbook (7^th Edition):

Che, Xiaohong. “Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.” 2011. Web. 23 Sep 2019.

Vancouver:

Che X. Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping. [Internet] [Thesis]. University of California – Riverside; 2011. [cited 2019 Sep 23]. 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

14. King, Emily Clark. Nutrient Modulators of Inflammation in Obese and Lean Adolescents.

Degree: Clinical Research, 2017, UCLA

URL: http://www.escholarship.org/uc/item/2m36n069

► Background: Obese individuals are at risk for iron deficiency due to both insufficient dietary iron intake and trapping of iron through an interleukin-6 (IL-6) dependent… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

King, E. C. (2017). Nutrient Modulators of Inflammation in Obese and Lean Adolescents. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/2m36n069

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

Chicago Manual of Style (16^th Edition):

King, Emily Clark. “Nutrient Modulators of Inflammation in Obese and Lean Adolescents.” 2017. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/2m36n069.

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

MLA Handbook (7^th Edition):

King, Emily Clark. “Nutrient Modulators of Inflammation in Obese and Lean Adolescents.” 2017. Web. 23 Sep 2019.

Vancouver:

King EC. Nutrient Modulators of Inflammation in Obese and Lean Adolescents. [Internet] [Thesis]. UCLA; 2017. [cited 2019 Sep 23]. Available from: http://www.escholarship.org/uc/item/2m36n069.

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

Council of Science Editors:

King EC. Nutrient Modulators of Inflammation in Obese and Lean Adolescents. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/2m36n069

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

UCLA

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

Degree: Biostatistics, 2014, UCLA

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

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Qiu, Jiaheng. “FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION.” 2014. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/1cj4b854.

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

MLA Handbook (7^th Edition):

Qiu, Jiaheng. “FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION.” 2014. Web. 23 Sep 2019.

Vancouver:

Qiu J. FINDING OPTIMAL EXPERIMENTAL DESIGNS FOR MODELS IN BIOMEDICAL STUDIES VIA PARTICLE SWARM OPTIMIZATION. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Sep 23]. 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

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

Degree: Biostatistics, 2015, UCLA

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

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Estes, Jason. “Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis.” 2015. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/03g42586.

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

MLA Handbook (7^th Edition):

Estes, Jason. “Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis.” 2015. Web. 23 Sep 2019.

Vancouver:

Estes J. Time Dynamic Modeling and Inference Approaches for Outcomes in Patients on Dialysis. [Internet] [Thesis]. UCLA; 2015. [cited 2019 Sep 23]. 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

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

Degree: Biostatistics, 2014, UCLA

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Lu, Xuyang. “Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome.” 2014. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/8223z6fp.

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

MLA Handbook (7^th Edition):

Lu, Xuyang. “Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome.” 2014. Web. 23 Sep 2019.

Vancouver:

Lu X. Bayesian Approaches for Instrumental Variable Analysis with Censored Time-to-Event Outcome. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Sep 23]. 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

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

Degree: Biostatistics, 2014, UCLA

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

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Han, Eunjung. “Addressing challenges for population genetic inference from next-generation sequencing.” 2014. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/87k8j8gg.

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

MLA Handbook (7^th Edition):

Han, Eunjung. “Addressing challenges for population genetic inference from next-generation sequencing.” 2014. Web. 23 Sep 2019.

Vancouver:

Han E. Addressing challenges for population genetic inference from next-generation sequencing. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Sep 23]. 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

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

Degree: Biostatistics, 2016, University of California – Berkeley

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

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Thesis, University of California – Berkeley. Accessed September 23, 2019. http://www.escholarship.org/uc/item/4zj7w7wv.

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

MLA Handbook (7^th Edition):

Tran, Linh Mai. “Comparative Causal Effect Estimation and Robust Variance for Longitudinal Data Structures with Applications to Observational HIV Treatment.” 2016. Web. 23 Sep 2019.

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 2019 Sep 23]. 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

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

Degree: Biostatistics, 2015, UCLA

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Wu, Sheng. “Optimal Design of Cluster Randomized Trials with Binary Outcomes.” 2015. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/0c5588qv.

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

MLA Handbook (7^th Edition):

Wu, Sheng. “Optimal Design of Cluster Randomized Trials with Binary Outcomes.” 2015. Web. 23 Sep 2019.

Vancouver:

Wu S. Optimal Design of Cluster Randomized Trials with Binary Outcomes. [Internet] [Thesis]. UCLA; 2015. [cited 2019 Sep 23]. 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

21. Polley, Eric. Super Learner.

Degree: Biostatistics, 2010, University of California – Berkeley

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Polley, Eric. “Super Learner.” 2010. Thesis, University of California – Berkeley. Accessed September 23, 2019. http://www.escholarship.org/uc/item/4qn0067v.

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

MLA Handbook (7^th Edition):

Polley, Eric. “Super Learner.” 2010. Web. 23 Sep 2019.

Vancouver:

Polley E. Super Learner. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2019 Sep 23]. 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

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

Degree: Biostatistics, 2013, University of California – Berkeley

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Ritter, Stephan Johannes. “Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data.” 2013. Thesis, University of California – Berkeley. Accessed September 23, 2019. http://www.escholarship.org/uc/item/600946rx.

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

MLA Handbook (7^th Edition):

Ritter, Stephan Johannes. “Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data.” 2013. Web. 23 Sep 2019.

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 2019 Sep 23]. 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

23. 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 (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Abdalla, Nada. “Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene.” 2018. Thesis, UCLA. Accessed September 23, 2019. http://www.escholarship.org/uc/item/89k1w808.

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

MLA Handbook (7^th Edition):

Abdalla, Nada. “Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene.” 2018. Web. 23 Sep 2019.

Vancouver:

Abdalla N. Parametric and Non-parametric Bayesian Modeling of Spatio-temporal Exposure Data in Industrial Hygiene. [Internet] [Thesis]. UCLA; 2018. [cited 2019 Sep 23]. 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

Harvard University

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

Degree: PhD, Biostatistics, 2012, Harvard University

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

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

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

Subjects/Keywords: biostatistics

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APA (6^th Edition):

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

Chicago Manual of Style (16^th Edition):

Snavely, Anna Catherine. “Multivariate Data Analysis with Applications to Cancer.” 2012. Doctoral Dissertation, Harvard University. Accessed September 23, 2019. http://nrs.harvard.edu/urn-3:HUL.InstRepos:9393266.

MLA Handbook (7^th Edition):

Snavely, Anna Catherine. “Multivariate Data Analysis with Applications to Cancer.” 2012. Web. 23 Sep 2019.

Vancouver:

Snavely AC. Multivariate Data Analysis with Applications to Cancer. [Internet] [Doctoral dissertation]. Harvard University; 2012. [cited 2019 Sep 23]. 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

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

Degree: PhD, Biostatistics, 2012, Harvard University

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

Chicago Manual of Style (16^th Edition):

White, Richard. “Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota.” 2012. Doctoral Dissertation, Harvard University. Accessed September 23, 2019. http://nrs.harvard.edu/urn-3:HUL.InstRepos:9795732.

MLA Handbook (7^th Edition):

White, Richard. “Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota.” 2012. Web. 23 Sep 2019.

Vancouver:

White R. Novel Statistical Methods Applied in Clinical Trials and Gut Microbiota. [Internet] [Doctoral dissertation]. Harvard University; 2012. [cited 2019 Sep 23]. 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

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

Degree: PhD, Biostatistics, 2013, Harvard University

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

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

Subjects/Keywords: Biostatistics

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

APA (6^th Edition):

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

Chicago Manual of Style (16^th Edition):

Braun, Danielle. “Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies.” 2013. Doctoral Dissertation, Harvard University. Accessed September 23, 2019. http://nrs.harvard.edu/urn-3:HUL.InstRepos:11744468.

MLA Handbook (7^th Edition):

Braun, Danielle. “Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies.” 2013. Web. 23 Sep 2019.

Vancouver:

Braun D. Statistical Methods to Adjust for Measurement Error in Risk Prediction Models and Observational Studies. [Internet] [Doctoral dissertation]. Harvard University; 2013. [cited 2019 Sep 23]. 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

University of Cincinnati

27. Ding, Siyang. A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013.

Degree: MS, Medicine: Biostatistics (Environmental Health), 2017, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1481032211809499

► AbstractChronic obstructive pulmonary disease (COPD) is a common disease. In the United States, current estimates suggest about 12 million people have been diagnosed with COPD,… (more)

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

Ding, S. (2017). A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1481032211809499

Chicago Manual of Style (16^th Edition):

Ding, Siyang. “A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013.” 2017. Masters Thesis, University of Cincinnati. Accessed September 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1481032211809499.

MLA Handbook (7^th Edition):

Ding, Siyang. “A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013.” 2017. Web. 23 Sep 2019.

Vancouver:

Ding S. A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013. [Internet] [Masters thesis]. University of Cincinnati; 2017. [cited 2019 Sep 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1481032211809499.

Council of Science Editors:

Ding S. A Prevalence Analysis of Hospital Admissions of Chronic Obstructive Pulmonary Disease in 2012 and 2013. [Masters Thesis]. University of Cincinnati; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1481032211809499

Boston University

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

Degree: PhD, Biostatistics, 2017, Boston University

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

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

Chicago Manual of Style (16^th Edition):

Kane, Elizabeth. “Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms.” 2017. Doctoral Dissertation, Boston University. Accessed September 23, 2019. http://hdl.handle.net/2144/27352.

MLA Handbook (7^th Edition):

Kane, Elizabeth. “Evaluating multiple imputation methods for longitudinal healthy aging index - a score variable with data missing due to death, dropout and several missing data mechanisms.” 2017. Web. 23 Sep 2019.

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 2019 Sep 23]. 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

29. 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 (6^th Edition):

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

Chicago Manual of Style (16^th Edition):

Liu, Xuan. “New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power.” 2015. Doctoral Dissertation, Boston University. Accessed September 23, 2019. http://hdl.handle.net/2144/15700.

MLA Handbook (7^th Edition):

Liu, Xuan. “New approach to compare treatments in adaptive seamless designs while maintaining Type I error and ensuring adequate power.” 2015. Web. 23 Sep 2019.

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 2019 Sep 23]. 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

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

Degree: 2015, Boston University

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

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

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

Subjects/Keywords: Biostatistics

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APA (6^th Edition):

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

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

Chicago Manual of Style (16^th Edition):

Lohsen, Mark. “Combined genome-wide association studies of cannabis dependence and personality traits.” 2015. Thesis, Boston University. Accessed September 23, 2019. http://hdl.handle.net/2144/16029.

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

MLA Handbook (7^th Edition):

Lohsen, Mark. “Combined genome-wide association studies of cannabis dependence and personality traits.” 2015. Web. 23 Sep 2019.

Vancouver:

Lohsen M. Combined genome-wide association studies of cannabis dependence and personality traits. [Internet] [Thesis]. Boston University; 2015. [cited 2019 Sep 23]. 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

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Open Access Theses and Dissertations