Statistics and Probability Commons^™

Statistics In The Billera-Holmes-Vogtmann Treespace, Grady S. Weyenberg

Theses and Dissertations--Statistics

This dissertation is an effort to adapt two classical non-parametric statistical techniques, kernel density estimation (KDE) and principal components analysis (PCA), to the Billera-Holmes-Vogtmann (BHV) metric space for phylogenetic trees. This adaption gives a more general framework for developing and testing various hypotheses about apparent differences or similarities between sets of phylogenetic trees than currently exists.

For example, while the majority of gene histories found in a clade of organisms are expected to be generated by a common evolutionary process, numerous other coexisting processes (e.g. horizontal gene transfers, gene duplication and subsequent neofunctionalization) will cause some genes to exhibit a …

Characteristics Associated With Willingness To Participate In A Randomized Controlled Behavioral Clinical Trial Using Home-Based Personal Computers And A Webcam, Hiroko H. Dodge, Yuriko Katsumata, Jian Zhu, Nora Mattek, Molly Bowman, Mattie Gregor, Katherine Wild, Jeffrey A Kaye

Biostatistics Faculty Publications

BACKGROUND: Trials aimed at preventing cognitive decline through cognitive stimulation among those with normal cognition or mild cognitive impairment are of significant importance in delaying the onset of dementia and reducing dementia prevalence. One challenge in these prevention trials is sample recruitment bias. Those willing to volunteer for these trials could be socially active, in relatively good health, and have high educational levels and cognitive function. These participants' characteristics could reduce the generalizability of study results and, more importantly, mask trial effects. We developed a randomized controlled trial to examine whether conversation-based cognitive stimulation delivered through personal computers, a webcam …

Identifying Genetic Variants For Heart Rate Variability In The Acetylcholine Pathway, Harriëtte Riese, Loretto M. Muñoz, Catharina A. Hartman, Xiuhua Ding, Shaoyong Su, Albertine J. Oldehinkel, Arie M. Van Roon, Peter J. Van Der Most, Joop Lefrandt, Ron T. Gansevoort, Pim Van Der Harst, Niek Verweij, Carmilla M. M. Licht, Dorret I. Boomsma, Jouke-Jan Hottenga, Gonneke Willemsen, Brenda W. J. H. Penninx, Ilja M. Nolte, Eco J. C. De Geus, Xiaoling Wang, Harold Snieder

Biostatistics Faculty Publications

Heart rate variability is an important risk factor for cardiovascular disease and all-cause mortality. The acetylcholine pathway plays a key role in explaining heart rate variability in humans. We assessed whether 443 genotyped and imputed common genetic variants in eight key genes (CHAT, SLC18A3, SLC5A7, CHRNB4, CHRNA3, CHRNA, CHRM2 and ACHE) of the acetylcholine pathway were associated with variation in an established measure of heart rate variability reflecting parasympathetic control of the heart rhythm, the root mean square of successive differences (RMSSD) of normal RR intervals. The association was studied in a …

Novel Image Markers For Non-Small Cell Lung Cancer Classification And Survival Prediction, Hongyuan Wang, Fuyong Xing, Hai Su, Arnold J. Stromberg, Lin Yang

Statistics Faculty Publications

BACKGROUND: Non-small cell lung cancer (NSCLC), the most common type of lung cancer, is one of serious diseases causing death for both men and women. Computer-aided diagnosis and survival prediction of NSCLC, is of great importance in providing assistance to diagnosis and personalize therapy planning for lung cancer patients.

RESULTS: In this paper we have proposed an integrated framework for NSCLC computer-aided diagnosis and survival analysis using novel image markers. The entire biomedical imaging informatics framework consists of cell detection, segmentation, classification, discovery of image markers, and survival analysis. A robust seed detection-guided cell segmentation algorithm is proposed to accurately …

Mixtures Of Self-Modelling Regressions, Rhonda D. Szczesniak, Kert Viele, Robin L. Cooper

Statistics Faculty Publications

A shape invariant model for functions f₁,...,f_n specifies that each individual function f_i can be related to a common shape function g through the relation f_i(x) = a_ig(c_ix + d_i) + b_i. We consider a flexible mixture model that allows multiple shape functions g₁,...,g_K, where each f_i is a shape invariant transformation of one of those g_K. We derive an MCMC algorithm for fitting the model using Bayesian Adaptive Regression Splines (BARS), propose …

Tissue Triage And Freezing For Models Of Skeletal Muscle Disease, Hui Meng, Paul M. L. Janssen, Robert W. Grange, Lin Yang, Alan H. Beggs, Lindsay C. Swanson, Stacy A. Cossette, Alison Frase, Martin K. Childers, Henk Granzier, Emanuela Gussoni, Michael W. Lawlor

Biostatistics Faculty Publications

Skeletal muscle is a unique tissue because of its structure and function, which requires specific protocols for tissue collection to obtain optimal results from functional, cellular, molecular, and pathological evaluations. Due to the subtlety of some pathological abnormalities seen in congenital muscle disorders and the potential for fixation to interfere with the recognition of these features, pathological evaluation of frozen muscle is preferable to fixed muscle when evaluating skeletal muscle for congenital muscle disease. Additionally, the potential to produce severe freezing artifacts in muscle requires specific precautions when freezing skeletal muscle for histological examination that are not commonly used when …

Genetic Analysis Workshop 18: Methods And Strategies For Analyzing Human Sequence And Phenotype Data In Members Of Extended Pedigrees, Heike Bickeböller, Julia N. Bailey, Joseph Beyene, Rita M. Cantor, Heather J. Cordell, Robert C. Culverhouse, Corinne D. Engelman, David W. Fardo, Saurabh Ghosh, Inke R. König, Justo Lorenzo Bermejo, Phillip E. Melton, Stephanie A. Santorico, Glen A. Satten, Lei Sun, Nathan L. Tintle, Andreas Ziegler, Jean W. Maccluer, Laura Almasy

Biostatistics Faculty Publications

Genetic Analysis Workshop 18 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence data from a pedigree-based sample. In this article we present an overview of the data sets and the contributions that analyzed these data. The family data, donated by the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples Consortium, included sequence-level genotypes based on sequencing and imputation, genome-wide association genotypes from prior genotyping arrays, and phenotypes from longitudinal assessments. The contributions from individual research groups were extensively discussed before, during, and after the workshop in theme-based discussion groups before being submitted …

On Family-Based Genome-Wide Association Studies With Large Pedigrees: Observations And Recommendations, David W. Fardo, Xue Zhang, Lili Ding, Hua He, Brad Kurowski, Eileen S. Alexander, Tesfaye B. Mersha, Valentina Pilipenko, Leah Kottyan, Kannabiran Nandakumar, Lisa Martin

Biostatistics Faculty Publications

Family based association studies are employed less often than case-control designs in the search for disease-predisposing genes. The optimal statistical genetic approach for complex pedigrees is unclear when evaluating both common and rare variants. We examined the empirical power and type I error rates of 2 common approaches, the measured genotype approach and family-based association testing, through simulations from a set of multigenerational pedigrees. Overall, these results suggest that much larger sample sizes will be required for family-based studies and that power was better using MGA compared to FBAT. Taking into account computational time and potential bias, a 2-step strategy …

Using Mendelian Inheritance Errors As Quality Control Criteria In Whole Genome Sequencing Data Set, Valentina V. Pilipenko, Hua He, Brad G. Kurowski, Eileen S. Alexander, Xue Zhang, Lili Ding, Tesfaye B. Mersha, Leah Kottyan, David W. Fardo, Lisa J. Martin

Biostatistics Faculty Publications

Although the technical and analytic complexity of whole genome sequencing is generally appreciated, best practices for data cleaning and quality control have not been defined. Family based data can be used to guide the standardization of specific quality control metrics in nonfamily based data. Given the low mutation rate, Mendelian inheritance errors are likely as a result of erroneous genotype calls. Thus, our goal was to identify the characteristics that determine Mendelian inheritance errors. To accomplish this, we used chromosome 3 whole genome sequencing family based data from the Genetic Analysis Workshop 18. Mendelian inheritance errors were provided as part …

A 2-Step Penalized Regression Method For Family-Based Next-Generation Sequencing Association Studies, Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang, David W. Fardo

Biostatistics Faculty Publications

Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.

Modeling Of Multivariate Longitudinal Phenotypes In Family Genetic Studies With Bayesian Multiplicity Adjustment, Lili Ding, Brad G. Kurowski, Hua He, Eileen S. Alexander, Tesfaye B. Mersha, David Fardo, Xue Zhang, Valentina V. Pilipenko, Leah Kottyan, Lisa J. Martin

Biostatistics Faculty Publications

Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family members. We developed a Bayesian model for analysis of bivariate quantitative traits measured longitudinally in family genetic studies. For a given trait, family-specific and subject-specific random effects account for correlation among family …

Abcc9 Gene Polymorphism Is Associated With Hippocampal Sclerosis Of Aging Pathology, Peter T. Nelson, Steven Estus, Erin L. Abner, Ishita Parikh, Manasi Malik, Janna H. Neltner, Eseosa Ighodaro, Wang-Xia Wang, Bernard R. Wilfred, Li-San Wang, Walter A. Kukull, Kannabiran Nandakumar, Mark L. Farman, Wayne W. Poon, Maria M. Corrada, Claudia H. Kawas, David H. Cribbs, David A. Bennett, Julie A. Schneider, Eric B. Larson, Paul K. Crane, Otto Valladares, Frederick A. Schmitt, Richard J. Kryscio, Gregory A. Jicha, Charles D. Smith, Stephen W. Scheff, Joshua A. Sonnen, Jonathan L. Haines, Margaret A. Pericak-Vance, Richard Mayeux, Lindsay A. Farrer, Linda J. Van Eldik, Craig Horbinski, Robert C. Green, Marla Gearing, Leonard W. Poon, Patricia L. Kramer, Randall L. Woltjer, Thomas J. Montine, Amanda B. Partch, Alexander J. Rajic, Katierose Richmire, Sarah E. Monsell, Gerard D. Schellenberg, David W. Fardo

Pathology and Laboratory Medicine Faculty Publications

Hippocampal sclerosis of aging (HS-Aging) is a high-morbidity brain disease in the elderly but risk factors are largely unknown. We report the first genome-wide association study (GWAS) with HS-Aging pathology as an endophenotype. In collaboration with the Alzheimer's Disease Genetics Consortium, data were analyzed from large autopsy cohorts: (#1) National Alzheimer's Coordinating Center (NACC); (#2) Rush University Religious Orders Study and Memory and Aging Project; (#3) Group Health Research Institute Adult Changes in Thought study; (#4) University of California at Irvine 90+ Study; and (#5) University of Kentucky Alzheimer's Disease Center. Altogether, 363 HS-Aging cases and 2,303 controls, all pathologically …

Self-Reported Head Injury And Risk Of Late-Life Impairment And Ad Pathology In An Ad Center Cohort, Erin L. Abner, Peter T. Nelson, Frederick A. Schmitt, Steven R. Browning, David W. Fardo, Lijie Wan, Gregory A. Jicha, Gregory E. Cooper, Charles D. Smith, Allison M. Caban-Holt, Linda J. Van Eldik, Richard J. Kryscio

Sanders-Brown Center on Aging Faculty Publications

Aims: To evaluate the relationship between self-reported head injury and cognitive impairment, dementia, mortality, and Alzheimer's disease (AD)-type pathological changes. Methods: Clinical and neuropathological data from participants enrolled in a longitudinal study of aging and cognition (n = 649) were analyzed to assess the chronic effects of self-reported head injury. Results: The effect of self-reported head injury on the clinical state depended on the age at assessment: for a 1-year increase in age, the OR for the transition to clinical mild cognitive impairment (MCI) at the next visit for participants with a history of head injury was 1.21 and 1.34 …

Multi-Tgdr, A Multi-Class Regularization Method, Identifies The Metabolic Profiles Of Hepatocellular Carcinoma And Cirrhosis Infected With Hepatitis B Or Hepatitis C Virus, Suyan Tian, Howard H. Chang, Chi Wang, Jing Jiang, Xiaomei Wang, Junqi Niu

Biostatistics Faculty Publications

BACKGROUND: Over the last decade, metabolomics has evolved into a mainstream enterprise utilized by many laboratories globally. Like other "omics" data, metabolomics data has the characteristics of a smaller sample size compared to the number of features evaluated. Thus the selection of an optimal subset of features with a supervised classifier is imperative. We extended an existing feature selection algorithm, threshold gradient descent regularization (TGDR), to handle multi-class classification of "omics" data, and proposed two such extensions referred to as multi-TGDR. Both multi-TGDR frameworks were used to analyze a metabolomics dataset that compares the metabolic profiles of hepatocellular carcinoma (HCC) …

A Bayesian Analysis Of The Spatial Concentration Of Individual Wealth In The Us North During The Nineteenth Century, Alice Kasakoff, Andrew Lawson, Emily Van Meter

Biostatistics Faculty Publications

Background: Kin effects can be difficult to distinguish from those of spatial proximity, since kin tend to live close to each other. Thus, past research showing correlations between the wealth of relatives may be showing the effects of proximity and shared locations, not the effects of kin.

Objective: What are the effects of kin and of spatial proximity upon wealth? This is studied both for fathers and sons and for brothers.

Methods: Data comes from a genealogical sample that has been linked to the US census of 1860. The genealogies allow us to identify fathers, sons, and …

Strengthening Interactions Between Statisticians And Collaborators: Objectives And Sample Sizes, Emily Van Meter, Richard Charnigo

Biostatistics Faculty Publications

No abstract provided.

The Initial Phases Of A Consistent Pricing System That Reflects The Online Sale Value Of A Horse, Curran A. Prettyman

Lewis Honors College Capstone Collection

Horses are one of the most uniquely priced commodities. This document provides a solution to an industry-wide weakness of inconsistent pricing and confusion. In the following report, an evaluation of the industry flaw is presented, an econometric approach is described in full, and a solution is proposed using insight gained from a regression analysis. This report uses an econometric approach to determine the impact of hunter jumper horse qualities on internet sale prices. Data is compiled from bigeq.com for seventy-eight horses in the states of Illinois, Indiana, Kentucky, Michigan, and Ohio. A linear regression analysis for twelve variables establishes that …

Contaminated Chi-Square Modeling And Its Application In Microarray Data Analysis, Feng Zhou

Theses and Dissertations--Statistics

Mixture modeling has numerous applications. One particular interest is microarray data analysis. My dissertation research is focused on the Contaminated Chi-Square (CCS) Modeling and its application in microarray. A moment-based method and two likelihood-based methods including Modified Likelihood Ratio Test (MLRT) and Expectation-Maximization (EM) Test are developed for testing the omnibus null hypothesis of no contamination of a central chi-square distribution by a non-central Chi-Square distribution. When the omnibus null hypothesis is rejected, we further developed the moment-based test and the EM test for testing an extra component to the Contaminated Chi-Square (CCS+EC) Model. The moment-based approach is easy and …

Genetic Association Testing Of Copy Number Variation, Yinglei Li

Theses and Dissertations--Statistics

Copy-number variation (CNV) has been implicated in many complex diseases. It is of great interest to detect and locate such regions through genetic association testings. However, the association testings are complicated by the fact that CNVs usually span multiple markers and thus such markers are correlated to each other. To overcome the difficulty, it is desirable to pool information across the markers. In this thesis, we propose a kernel-based method for aggregation of marker-level tests, in which first we obtain a bunch of p-values through association tests for every marker and then the association test involving CNV is based on …

Natural Phenomena As Potential Influence On Social And Political Behavior: The Earth’S Magnetic Field, Jackie R. East

Theses and Dissertations--Political Science

Researchers use natural phenomena in a number of disciplines to help explain human behavioral outcomes. Research regarding the potential effects of magnetic fields on animal and human behavior indicates that fields could influence outcomes of interest to social scientists. Tests so far have been limited in scope. This work is a preliminary evaluation of whether the earth’s magnetic field influences human behavior it examines the baseline relationship exhibited between geomagnetic readings and a host of social and political outcomes. The emphasis on breadth of topical coverage in these statistical trials, rather than on depth of development for any one model, …

A Fault-Based Model Of Fault Localization Techniques, Mark A. Hays

Theses and Dissertations--Computer Science

Every day, ordinary people depend on software working properly. We take it for granted; from banking software, to railroad switching software, to flight control software, to software that controls medical devices such as pacemakers or even gas pumps, our lives are touched by software that we expect to work. It is well known that the main technique/activity used to ensure the quality of software is testing. Often it is the only quality assurance activity undertaken, making it that much more important.

In a typical experiment studying these techniques, a researcher will intentionally seed a fault (intentionally breaking the functionality of …

Normal Mixture And Contaminated Model With Nuisance Parameter And Applications, Qian Fan

Theses and Dissertations--Statistics

This paper intend to find the proper hypothesis and test statistic for testing existence of bilaterally contamination when there exists nuisance parameter. The test statistic is based on method of moments estimators. Union-Intersection test is used for testing if the distribution of population can be implemented by a bilaterally contaminated normal model with unknown variance. This paper also developed a hierarchical normal mixture model (HNM) and applied it to birth weight data. EM algorithm is employed for parameter estimation and a singular Bayesian information criterion (sBIC) is applied to choose the number components. We also proposed a singular flexible information …

Fusarium Head Blight Resistance And Agronomic Performance In Soft Red Winter Wheat Populations, Daniela Sarti Dvorjak

Theses and Dissertations--Plant and Soil Sciences

Fusarium head blight (FHB), caused by Fusarium graminearum Schwabe [telomorph: Gibberella zeae Schwein.(Petch)], is recognized as one of the most destructive diseases of wheat (Triticum aestivum L. and T. durum L.) and barley (Hordeum vulgare L.) worldwide. Breeding for FHB resistance must be accompanied by selection for desirable agronomic traits. Donor parents with two FHB resistance quantitative trait loci (QTL) Fhb1 (chromosome 3BS) and QFhs.nau-2DL (chromosome 2DL) were crossed to four adapted SRW wheat lines to generate backcross and forward cross progeny. F₂ individuals were genotyped and assigned to 4 different groups according to presence/ absence of …

Economic Challenges Facing Kentucky’S Electricity Generation Under Greenhouse Gas Constraints, Energy And Environment Cabinet, Commonwealth Of Kentucky, Department Of Statistics, University Of Kentucky, Center For Applied Energy Research, University Of Kentucky, Pacific Northwest National Laboratory

Statistics Reports

From the preface:

For the Energy and Environment Cabinet (EEC), which has primacy in administering most federal environmental laws and regulations at the state level, we have to understand the implications of what is arguably one of the most challenging issues to confront us—greenhouse gas (GHG) emissions and their impact on climate change. Efforts to reduce GHG or carbon dioxide (CO₂) emissions have moved beyond the point of discussion at the national level, and the United States Supreme Court has ruled that the U.S. Environmental Protection Agency (EPA) has the authority to regulate GHG emissions. Furthermore, while public …

Approximate Techniques In Solving Optimal Camera Placement Problems, Jian Zhao, Ruriko Yoshida, Sen-Ching Samson Cheung, David Haws

Statistics Faculty Publications

While the theoretical foundation of the optimal camera placement problem has been studied for decades, its practical implementation has recently attracted significant research interest due to the increasing popularity of visual sensor networks. The most flexible formulation of finding the optimal camera placement is based on a binary integer programming (BIP) problem. Despite the flexibility, most of the resulting BIP problems are NP-hard and any such formulations of reasonable size are not amenable to exact solutions. There exists a myriad of approximate algorithms for BIP problems, but their applications, efficiency, and scalability in solving camera placement are poorly understood. Thus, …

Risk Score Modeling Of Multiple Gene To Gene Interactions Using Aggregated-Multifactor Dimensionality Reduction, Hongying Dai, Richard J. Charnigo, Mara L. Becker, J. Steven Leeder, Alison A. Motsinger-Reif

Statistics Faculty Publications

BACKGROUND: Multifactor Dimensionality Reduction (MDR) has been widely applied to detect gene-gene (GxG) interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk) from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account.

RESULTS: We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR) method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification …

A Neural Network Model To Translate Brain Developmental Events Across Mammalian Species, Radhakrishnan Nagarajan, Jeffrey N. Jonkman

Biostatistics Faculty Publications

Translating the timing of brain developmental events across mammalian species using suitable models has provided unprecedented insights into neural development and evolution. More importantly, these models can prove to be useful abstractions and predict unknown events across species from known empirical event timing data retrieved from published literature. Such predictions can be especially useful since the distribution of the event timing data is skewed with a majority of events documented only across a few selected species. The present study investigates the choice of single hidden layer feed-forward neural networks (FFNN) for predicting the unknown events from the empirical data. A …

The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins

Theses and Dissertations--Epidemiology and Biostatistics

Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents …

Data Mining And Pattern Discovery Using Exploratory And Visualization Methods For Large Multidimensional Datasets, Hsin-Fang Li

Theses and Dissertations--Epidemiology and Biostatistics

Oral health problems have been a major public health concern profoundly affecting people’s general health and quality of life. Given that oral health data is composed of several measurable dimensions including clinical measurements, socio-behavioral factors, genetic predispositions, self-reported assessments, and quality of life measures, strategies for analyzing multidimensional data are neither computationally straightforward nor efficient. Researchers face major challenges to identify tools that circumvent the processes of manually probing the data.

The purpose of this dissertation is to provide applications of the proposed methodology on oral health-related data that go beyond identifying risk factors from a single dimension, and to …

Analysis Of Spatial Data, Xiang Zhang

Theses and Dissertations--Statistics

In many areas of the agriculture, biological, physical and social sciences, spatial lattice data are becoming increasingly common. In addition, a large amount of lattice data shows not only visible spatial pattern but also temporal pattern (see, Zhu et al. 2005). An interesting problem is to develop a model to systematically model the relationship between the response variable and possible explanatory variable, while accounting for space and time effect simultaneously.

Spatial-temporal linear model and the corresponding likelihood-based statistical inference are important tools for the analysis of spatial-temporal lattice data. We propose a general asymptotic framework for spatial-temporal linear models and …