Statistics and Probability Commons^™

A General Approach To Detect Gene (G)-Environment (E) Additive Interaction Leveraging G-E Independence In Case-Control Studies, Eric Tchetgen Tchetgen, Tamar Sofer, Benedict H.W. Wong

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Novel Targeted Learning Method For Quantitative Trait Loci Mapping, Hui Wang, Zhongyang Zhang, Sherri Rose, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We present a novel semiparametric method for quantitative trait loci (QTL) mapping in experimental crosses. Conventional genetic mapping methods typically assume parametric models with Gaussian errors and obtain parameter estimates through maximum likelihood estimation. In contrast with univariate regression and interval mapping methods, our model requires fewer assumptions and also accommodates various machine learning algorithms. Estimation is performed with targeted maximum likelihood learning methods. We demonstrate our semiparametric targeted learning approach in a simulation study and a well-studied barley dataset.

Strategic Focus On 3r Principles Reveals Major Reductions In The Use Of Animals In Pharmaceutical Toxicity Testing, Elin Törnqvist, Anita Annas, Britta Granath, Elisabeth Jalkesten, Ian Cotgreave, Mattias Öberg

Application of Alternative Methods Collection

The principles of the 3Rs, Replacement, Reduction and Refinement, are being increasingly incorporated into legislations, guidelines and practice of animal experiments in order to safeguard animal welfare. In the present study we have studied the systematic application of 3R principles to toxicological research in the pharmaceutical industry, with particular focus on achieving reductions in animal numbers used in regulatory and investigatory in vivo studies. The work also details major factors influencing these reductions including the conception of ideas, cross-departmental working and acceptance into the work process. Data from 36 reduction projects were collected retrospectively from work between 2006 and 2010. …

A Note On The Control Function Approach With An Instrumental Variable And A Binary Outcome, Eric Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Simple Regression-Based Approach To Account For Survival Bias In Birth Outcomes Research, Eric J. Tchetgen Tchetgen, Kelesitse Phiri, Roger Shapiro

Harvard University Biostatistics Working Paper Series

No abstract provided.

Entering The Era Of Data Science: Targeted Learning And The Integration Of Statistics And Computational Data Analysis, Mark J. Van Der Laan, Richard J.C.M. Starmans

U.C. Berkeley Division of Biostatistics Working Paper Series

This outlook article will appear in Advances in Statistics and it reviews the research of Dr. van der Laan's group on Targeted Learning, a subfield of statistics that is concerned with the construction of data adaptive estimators of user-supplied target parameters of the probability distribution of the data and corresponding confidence intervals, aiming to only rely on realistic statistical assumptions. Targeted Learning fully utilizes the state of the art in machine learning tools, while still preserving the important identity of statistics as a field that is concerned with both accurate estimation of the true target parameter value and assessment of …

Control Function Assisted Ipw Estimation With A Secondary Outcome In Case-Control Studies, Tamar Sofer, Marilyn C. Cornelis, Peter Kraft, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Reduced Major Axis Regression: Teaching Alternatives To Least Squares, William V. Harper

Mathematics Faculty Scholarship

The theoretical underpinnings of standard least squares regression analysis are based on the assumption that the independent variable (often thought of as x) is measured without error as a design variable. The dependent variable (often labeled y) is modeled as having uncertainty or error. Both independent and dependent measurements may have multiple sources of error. Thus the underlying least squares regression assumptions can be violated. Reduced Major Axis (RMA) regression is specifically formulated to handle errors in both the x and y variables. It is an excellent topic to teach students the importance of understanding the assumptions underlying the statistical …

What Is Higher Mathematics? Why Is It So Hard To Interpret? What Can Be Done?, John Tabak

Journal of Interpretation

Courses and seminars in higher mathematics are some of the most challenging assignments faced by academic interpreters. Difficulties interpreting higher mathematics can adversely impact the academic and professional aspirations of deaf mathematics students and professionals. This paper discusses the nature of higher mathematics with the goal of identifying what distinguishes higher mathematics from other subjects; it then reviews the history of attempts to sign/interpret higher mathematics with particular attention to current challenges associated with expressing higher mathematics in sign. The final part of the paper discusses strategies for more effectively expressing higher mathematics in American Sign Language.

Statistical Modeling And Prediction Of Hiv/Aids Prognosis: Bayesian Analyses Of Nonlinear Dynamic Mixtures, Xiaosun Lu

USF Tampa Graduate Theses and Dissertations

Statistical analyses and modeling have contributed greatly to our understanding of the pathogenesis of HIV-1 infection; they also provide guidance for the treatment of AIDS patients and evaluation of antiretroviral (ARV) therapies. Various statistical methods, nonlinear mixed-effects models in particular, have been applied to model the CD4 and viral load trajectories. A common assumption in these methods is all patients come from a homogeneous population following one mean trajectories. This assumption unfortunately obscures important characteristic difference between subgroups of patients whose response to treatment and whose disease trajectories are biologically different. It also may lack the robustness against population heterogeneity …

Association Between Class Iii Obesity (Bmi Of 40-59 Kg/M2) And Mortality: A Pooled Analysis Of 20 Prospective Studies, Cari M. Kitahara, Alan J. Flint, Amy Berrington De Gonzalez, Leslie Bernstein, Michelle Brotzman, Kim Robien, +30 Additional Authors

Epidemiology Faculty Publications

Background

The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity.

Methods and Findings

In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per …

Super-Learning Of An Optimal Dynamic Treatment Rule, Alexander R. Luedtke, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider the estimation of an optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric, beyond possible knowledge about the treatment and censoring mechanisms. We propose data adaptive estimators of this optimal dynamic regime which are defined by sequential loss-based learning under both the blip function and weighted classification frameworks. Rather than \textit{a priori} selecting …

Targeted Learning Of The Mean Outcome Under An Optimal Dynamic Treatment Rule, Mark J. Van Der Laan, Alexander R. Luedtke

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider estimation of and inference for the mean outcome under the optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric beyond possible knowledge about the treatment and censoring mechanism. This contrasts from the current literature that relies on parametric assumptions. We establish that the mean of the counterfactual outcome under the optimal dynamic treatment …

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 …

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 …

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 …

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 …

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 …

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 …

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 …