Statistics and Probability Commons^™

An Evaluation Of Florida Gulf Coast University's Residence Life Staff Member's Hurricane Preparedness, Erin Floto

USF Tampa Graduate Theses and Dissertations

Florida Gulf Coast University (FGCU) is located along the coast of the Gulf of Mexico in southern Florida, in an area vulnerable to hurricane strikes. At FGCU, The Office of Housing and Residence Life (OHRL) is responsible for three locations on- and off-campus where students reside in apartment or suite-style housing. Due to the large number of students with varying backgrounds, the OHRL staff members have become essential personnel during severe weather events that may cause safety concerns for the residents living in OHRL housing locations. This study's purpose is to assess the Residence Life staff on their level of …

Predicting The Future Subject's Outcome Via An Optimal Stratification Procedure With Baseline Information, Florence H. Yong, Lu Tian, Sheng Yu, Tianxi Cai, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Improvements On Segment Based Contours Method For Dna Microarray Image Segmentation, Yang Li

Doctoral Dissertations

DNA microarray is an efficient biotechnology tool for scientists to measure the expression levels of large numbers of genes, simultaneously. To obtain the gene expression, microarray image analysis needs to be conducted. Microarray image segmentation is a fundamental step in the microarray analysis process. Segmentation gives the intensities of each probe spot in the array image, and those intensities are used to calculate the gene expression in subsequent analysis procedures. Therefore, more accurate and efficient microarray image segmentation methods are being pursued all the time.

In this dissertation, we are making efforts to obtain more accurate image segmentation results. We …

Common Method Variance: An Experimental Manipulation, Alison Wall

Doctoral Dissertations

Although common method variance has been a subject of research concern for over fifty years, its influence on study results is still not well understood. Common method variance concerns are frequently cited as an issue in the publication of self-report data; yet, there is no consensus as to when, or if, common method variance creates bias. This dissertation examines common method variance by approaching it from an experimental standpoint. If groups of respondents can be influenced to vary their answers to survey items based upon the presence or absence of procedural remedies, a better understanding of common method variance can …

Modeling Spatial Covariance Functions, Inkyung Choi

Open Access Dissertations

Covariance modeling plays a key role in the spatial data analysis as it provides important information about the dependence structure of underlying processes and determines performance of spatial prediction. Various parametric models have been developed to accommodate the idiosyncratic features of a given dataset. However, the parametric models may impose unjustified restrictions to the covariance structure and the procedure of choosing a specific model is often ad-hoc. In the first part of the dissertation, a new nonparametric covariance model that can avoid the choice of parametric forms is proposed. The estimator is obtained via a nonparametric approximation of completely monotone …

Better Physical Activity Classification Using Smartphone Acceleration Sensor, Muhammad Arif, Mohsin Bilal, Ahmed Kattan, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted …

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 …

Quantitative Evidence For The Use Of Simulation And Randomization In The Introductory Statistics Course, Nathan L. Tintle, Ally Rogers, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

Faculty Work Comprehensive List

The use of simulation and randomization in the introductory statistics course is gaining popularity, but what evidence is there that these approaches are improving students’ conceptual understanding and attitudes as we hope? In this talk I will discuss evidence from early full-length versions of such a curriculum, covering issues such as (a) items and scales showing improved conceptual performance compared to traditional curriculum, (b) transferability of findings to different institutions, (c) retention of conceptual understanding post-course and (d) student attitudes. Along the way I will discuss a few areas in which students in both simulation/randomization courses and the traditional course …

Trends And Determinants Of Up-To-Date Status With Colorectal Cancer Screening In Tennessee, 2002-2008, Sreenivas P. Veeranki, Shimin Zheng

ETSU Faculty Works

BACKGROUND:

Screening rates for colorectal cancer (CRC) are increasing nationwide including Tennessee (TN); however, their up-to-date status is unknown. The objective of this study is to determine the trends and characteristics of TN adults who are up-to-date status with CRC screening during 2002-2008.

METHODS:

We examined data from the TN Behavioral Risk Factor Surveillance System for 2002, 2004, 2006 and 2008 to estimate the proportion of respondents aged 50 years and above who were up-to-date status with CRC screening, defined as an annual home fecal occult blood test and/or sigmoidoscopy or colonoscopy in the past 5 years. We identified trends …

Bivariate Doubly Inflated Poisson And Related Regression Models, Pooja Sengupta

Mathematics & Statistics Theses & Dissertations

Count data are common in observational scientific investigations, and in many instances, such as twin or crossover studies, the data consists of dependent bivariate counts. An appropriate model for such data is the bivariate Poisson distribution given in Kocherlakota and Kocherlakota (2001). However, in situations where inflated count of (0, 0) occur, Lee et al. (2009) proposed the zero-inflated bivariate Poisson distribution which accounts for the inflated count. In this research, we introduce and study a bivariate distribution that accounts for an inflated count of the (k, k) cell for some k>0, in addition to the …

Stochastic Modeling And Analysis Of Energy Commodity Spot Price Processes, Olusegun Michael Otunuga

USF Tampa Graduate Theses and Dissertations

Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand

expectation process. In order to be able to understand the price balancing process, it is important to know the economic forces and the behavior of energy commodity spot price processes. The relationship between the different energy sources and its utility together with uncertainty also play a role in many important energy issues.

The qualitative and quantitative behavior of energy commodities in which the trend in price of one commodity coincides with the trend in price of …

Rationale, Design, And Baseline Characteristics Of A Randomized, Placebo-Controlled Cardiovascular Outcome Trial Of Empagliflozin (Empa-Reg Outcometm), Bernard Zinman, Silvio E. Inzucchi, John M. Lachin, Christoph Wanner, Roberto Ferrari, David Fitchett, Erich Bluhmki, Stefan Hantel, Joan Kempthorne-Rawson, Jennifer Newman, Odd Erik Johansen, Hans Juergen Woerle, Uli C. Broedl

Epidemiology Faculty Publications

Background

Evidence concerning the importance of glucose lowering in the prevention of cardiovascular (CV) outcomes remains controversial. Given the multi-faceted pathogenesis of atherosclerosis in diabetes, it is likely that any intervention to mitigate this risk must address CV risk factors beyond glycemia alone. The SGLT-2 inhibitor empagliflozin improves glucose control, body weight and blood pressure when used as monotherapy or add-on to other antihyperglycemic agents in patients with type 2 diabetes. The aim of the ongoing EMPA-REG OUTCOMETM trial is to determine the long-term CV safety of empagliflozin, as well as investigating potential benefits on microvascular outcomes.

Methods

Patients who …

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 …

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 …

Evaluation Of The Power And Type 1 Error Of Recently Proposed Family-Based Tests Of Assocations For Rare Variants, Allison Hainline, Carolina Alvarez, Alexander Luedtke, Brian Greco, Andrew Beck, Nathan L. Tintle

Faculty Work Comprehensive List

Until very recently, few methods existed to analyze rare-variant association with binary phenotypes in complex pedigrees. We consider a set of recently proposed methods applied to the simulated and real hypertension phenotype as part of the Genetic Analysis Workshop 18. Minimal power of the methods is observed for genes containing variants with weak effects on the phenotype. Application of the methods to the real hypertension phenotype yielded no genes meeting a strict Bonferroni cutoff of significance. Some prior literature connects 3 of the 5 most associated genes (p <1 × 10−4) to hypertension or related phenotypes. Further methodological development is needed to extend these methods to handle covariates, and to explore more powerful test alternatives.

Evaluating The Concordance Between Sequencing, Imputation And Microarray Genotype Calls In The Gaw18 Data, Ally Rogers, Andrew Beck, Nathan L. Tintle

Faculty Work Comprehensive List

Genotype errors are well known to increase type I errors and/or decrease power in related tests of genotypephenotype association, depending on whether the genotype error mechanism is associated with the phenotype. These relationships hold for both single and multimarker tests of genotype-phenotype association. To assess the potential for genotype errors in Genetic Analysis Workshop 18 (GAW18) data, where no gold standard genotype calls are available, we explored concordance rates between sequencing, imputation, and microarray genotype calls. Our analysis shows that missing data rates for sequenced individuals are high and that there is a modest amount of called genotype discordance between …

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

Faculty Work Comprehensive List

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 …

Application Of Family-Based Tests Of Association For Rare Variants To Pathways, Brian Greco, Alexander Luedtke, Allison Hainline, Carolina Alvarez, Andrew Beck, Nathan L. Tintle

Faculty Work Comprehensive List

Pathway analysis approaches for sequence data typically either operate in a single stage (all variants within all genes in the pathway are combined into a single, very large set of variants that can then be analyzed using standard “gene-based” test statistics) or in 2-stages (gene-based p values are computed for all genes in the pathway, and then the gene-based p values are combined into a single pathway p value). To date, little consideration has been given to the performance of gene-based tests (typically designed for a smaller number of single-nucleotide variants [SNVs]) when the number of SNVs in the gene …

Interadapt -- An Interactive Tool For Designing And Evaluating Randomized Trials With Adaptive Enrollment Criteria, Aaron Joel Fisher, Harris Jaffee, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

The interAdapt R package is designed to be used by statisticians and clinical investigators to plan randomized trials. It can be used to determine if certain adaptive designs offer tangible benefits compared to standard designs, in the context of investigators’ specific trial goals and constraints. Specifically, interAdapt compares the performance of trial designs with adaptive enrollment criteria versus standard (non-adaptive) group sequential trial designs. Performance is compared in terms of power, expected trial duration, and expected sample size. Users can either work directly in the R console, or with a user-friendly shiny application that requires no programming experience. Several added …

Vitamin D Status And Demographic And Lifestyle Determinants Among Adults In The United States (Nhanes 2001-2006), Yan Cao, Katie L. Callahan, Sreenivas P. Veeranki, Yang Chen, Ying Liu, Shimin Zheng

ETSU Faculty Works

This study looked at risk factors associated with vitamin D levels in the body among a representative sample of adults in the U.S., NHANES III (2001-2006) data were used to assess the relationship between several demographic and health risk factors and vitamin D levels in the body. The Baseline-Category Logit Model was used to test the association between vitamin D level and the potential risk factors age, education, ethnicity, poverty status, physical activity, smoking, alcohol, obesity, diabetes and total cholesterol with both genders. Vitamin D insufficiency and deficiency were significantly associated with age, race, education, physical activity, obesity, diabetes and …

The Impact Of Student Performance On Large-Scale Assessments: A View Of Long-Term Health, Career, And Societal Outcomes, Roman Usatin

Seton Hall University Dissertations and Theses (ETDs)

This study examined the predictive power of student growth for large-scale assessments on meaningful life outcomes, focusing on the three categories of health, career, and societal involvement. Analysis was conducted using the NELS:88/00 dataset–a longitudinal study that followed a nationally-representative sample of over 12,000 eighth grade students from 1988 to 2000, until the students were 26 years old and entered into the work force. The large-scale assessment variables included math and reading performance in the 1988 cognitive batteries administered by NELS. To gauge growth levels, I generated Student Growth Percentiles (SGP) from tests administered by NELS from 1988 to 1992. …

Methods For Exploring Treatment Effect Heterogeneity In Subgroup Analysis: An Application To Global Clinical Trials, I. Manjula Schou, Ian C. Marschner

COBRA Preprint Series

Multi-country randomised clinical trials (MRCTs) are common in the medical literature and their interpretation has been the subject of extensive recent discussion. In many MRCTs, an evaluation of treatment effect homogeneity across countries or regions is conducted. Subgroup analysis principles require a significant test of interaction in order to claim heterogeneity of treatment effect across subgroups, such as countries in a MRCT. As clinical trials are typically underpowered for tests of interaction, overly optimistic expectations of treatment effect homogeneity can lead researchers, regulators and other stakeholders to over-interpret apparent differences between subgroups even when heterogeneity tests are insignificant. In this …

How Sexism Makes The Man: Examining The Relationship Between Masculinity, Ambivalent Sexism, And Gender Stereotyping, Mariah L. Wilkerson

Lawrence University Honors Projects

Masculinity is a precarious social status, meaning it can be lost through social and gender transgressions (Bosson & Vandello, 2011). Men often act in stereotypically masculine ways to reassert their masculinity and restore their social status after it has been threatened. The current study also examines masculinity in a new way, as a collective gender identity (e.g., Tajfel, 1982). I hypothesized that threatened men and men who identify as more masculine will display masculinity through more polarized attitudes towards traditional and nontraditional groups of men and women, endorsing traditional gender stereotypes, and intensified ambivalently sexist attitudes. Two empirical studies tested …

Trend Analysis And Modeling Of Health And Environmental Data: Joinpoint And Functional Approach, Ram C. Kafle

USF Tampa Graduate Theses and Dissertations

The present study is divided into two parts: the first is on developing the statistical analysis and modeling of mortality (or incidence) trends using Bayesian joinpoint regression and the second is on fitting differential equations from time series data to derive the rate of change of carbon dioxide in the atmosphere.

Joinpoint regression model identifies significant changes in the trends of the incidence, mortality, and survival of a specific disease in a given population. Bayesian approach of joinpoint regression is widely used in modeling statistical data to identify the points in the trend where the significant changes occur. The purpose …

Pgs: A Tool For Association Study Of High-Dimensional Microrna Expression Data With Repeated Measures, Yinan Zheng, Zhe Fei, Wei Zhang, Justin Starren, Lei Liu, Andrea Baccarelli, Yi Li, Lifang Hou

The University of Michigan Department of Biostatistics Working Paper Series

Motivation: MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Due to interested in the dynamic nature of the miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNAs expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used site-by-site multiple testing may impair the value of repeated or multiple measures data by ignoring the inherent dependent structure, which lead to problems including underpowered results after multiple comparison …

Targeted Maximum Likelihood Estimation Using Exponential Families, Iván Díaz, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

Targeted maximum likelihood estimation (TMLE) is a general method for estimating parameters in semiparametric and nonparametric models. Each iteration of TMLE involves fitting a parametric submodel that targets the parameter of interest. We investigate the use of exponential families to define the parametric submodel. This implementation of TMLE gives a general approach for estimating any smooth parameter in the nonparametric model. A computational advantage of this approach is that each iteration of TMLE involves estimation of a parameter in an exponential family, which is a convex optimization problem for which software implementing reliable and computationally efficient methods exists. We illustrate …

Flint International Statistics Conference Agenda, Kettering University

Flint: One City, 100 Years of Variability

Conference Agenda—Keynote Speakers, Invited & Contributed Talks, Posters, Field Trips

• Tuesday, June 24
• Wednesday, June 25
• Thursday, June 26
• Friday, June 27
• Saturday, June 28

Select Sessions:

• Elart von Collani “Statistics as a general tool for all sciences.”
• Francesca Greselin “Measuring inequality at the time of the Great Divergence.”
• Ernest Fokoue “Recent Applications of Statistical Data Mining for Big Data Predictive Analysis.”
• Vladimir Kaishev “Probability and statistics in actuarial applications.”
• Galia Novikova “Data Mining for Software Development Quality Management.”
• Leda Minkova “Stochastic Models and Statistical Applications.”
• Krzysztof Podgorski “Non-Gaussian stochastic models: theory and applications.”
• Kristina Sendova “Risk measures, probability measures …