Applied Statistics Commons^™

Examining The Literature On “Networks In Space And In Time.” An Introduction, Luca De Benedictis, Prosperina Vitale, Stanley Wasserman

Luca De Benedictis

The Network science special issue of “Networks in space and in time: methods and applications” contributes to the debate on contextual analysis in network science. It includes seven research papers that shed light on the analysis of network phenomena studied within geographic space and across temporal dimensions. In these papers, methodological issues as well as specific applications are described from different fields. We take the seven papers, study their citations and texts, and relate them to the broader literature. By exploiting the bibliographic information and the textual data of these seven documents, citation analysis and lexical correspondence analysis allow us …

Dialectical Behavior Therapy For High Suicide Risk In Individuals With Borderline Personality Disorder: A Randomized Clinical Trial And Component Analysis, Marsha M. Linehan, Kathryn E. Korslund, Melanie S. Harned, Robert J. Gallop, Anita Lungu, Andrada D. Neacsiu, Joshua Mcdavid, Katherine Anne Comtois, Angela M. Murray-Gregory

Mathematics Faculty Publications

No abstract provided.

An Assessment Of The Performances Of Several Univariate Tests Of Normality, James Olusegun Adefisoye

FIU Electronic Theses and Dissertations

The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when …

Predicting Successful Long-Term Weight Loss From Short-Term Weight-Loss Outcomes: New Insights From A Dynamic Energy Balance Model (The Pounds Lost Study), Diana Thomas, W Andrada Ivanescu, Corby K. Martin, Steven B. Heymsfield, Kaitlyn Marshall, Victoria E. Bodrato, Donald Williamson, Stephen Anton, Frank M. Sacks, Donna Ryan, George A. Bray

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds.

Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1.

Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, …

Judge-Jury Agreement In Criminal Cases: A Partial Replication Of Kalven And Zeisel's The American Jury, Theodore Eisenberg, Paula L. Hannaford-Agor, Valerie P. Hans, Nicole L. Waters, G. Thomas Munsterman, Stewart J. Schwab, Martin T. Wells

Stewart J Schwab

This study uses a new criminal case data set to partially replicate Kalven and Zeisel's classic study of judge-jury agreement. The data show essentially the same rate of judge-jury agreement as did Kalven and Zeisel for cases tried almost 50 years ago. This study also explores judge-jury agreement as a function of evidentiary strength (as reported by both judges and juries), evidentiary complexity (as reported by both judges and juries), legal complexity (as reported by judges), and locale. Regardless of which adjudicator's view of evidentiary strength is used, judges tend to convict more than juries in cases of "middle" evidentiary …

An Empirical Analysis Of Ceo Employment Contracts: What Do Top Executives Bargain For?, Stewart J. Schwab, Randall S. Thomas

Stewart J Schwab

No abstract provided.

How Employment-Discrimination Plaintiffs Fare In The Federal Courts Of Appeals, Kevin M. Clermont, Theodore Eisenberg, Stewart J. Schwab

Stewart J Schwab

Employment-discrimination plaintiffs swim against the tide. Compared to the typical plaintiff, they win a lower proportion of cases during pretrial and after trial. Then, many of their successful cases are appealed. On appeal, they have a harder time in upholding their successes, as well in reversing adverse outcome. This tough story does not describe some tiny corner of the litigation world. Employment-discrimination cases constitute an increasing fraction of the federal civil docket, now reigning as the largest single category of cases at nearly 10 percent. In this article, we use official government data to describe the appellate phase of this …

Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh

Maher Qumsiyeh

Efron’s (1979) Bootstrap has been shown to be an effective method for statistical estimation and testing. It provides better estimates than normal approximations for studentized means, least square estimates and many other statistics of interest. It can be used to select the active factors - factors that have an effect on the response - in experimental designs. This article shows that the bootstrap can be used to determine sample size or the number of runs required to achieve a certain confidence level in statistical experiments.

Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy

Maher Qumsiyeh

Experimental situations in which observations are not normally distributed frequently occur in practice. A common situation occurs when responses are discrete in nature, for example counts. One way to analyze such experimental data is to use a transformation for the responses; another is to use a link function based on a generalized linear model (GLM) approach. Re-sampling is employed as an alternative method to analyze non-normal, discrete data. Results are compared to those obtained by the previous two methods.

Modeling Neurovascular Coupling From Clustered Parameter Sets For Multimodal Eeg-Nirs, M. Tanveer Talukdar, H. Robert Frost, Solomon G. G. Diamond

Dartmouth Scholarship

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation. The approach is evaluated first with simulated EEG-NIRS data and then by applying the method to experimental EEG-NIRS data measured from …

Best Practice Recommendations For Data Screening, Justin A. Desimone, Peter D. Harms, Alice J. Desimone

Department of Management: Faculty Publications

Survey respondents differ in their levels of attention and effort when responding to items. There are a number of methods researchers may use to identify respondents who fail to exert sufficient effort in order to increase the rigor of analysis and enhance the trustworthiness of study results. Screening techniques are organized into three general categories, which differ in impact on survey design and potential respondent awareness. Assumptions and considerations regarding appropriate use of screening techniques are discussed along with descriptions of each technique. The utility of each screening technique is a function of survey design and administration. Each technique has …

Marginal Structural Models: An Application To Incarceration And Marriage During Young Adulthood, Valerio Bacak, Edward Kennedy

Edward H. Kennedy

Advanced methods for panel data analysis are commonly used in research on family life and relationships, but the fundamental issue of simultaneous time-dependent confounding and mediation has received little attention. In this article the authors introduce inverse-probability-weighted estimation of marginal structural models, an approach to causal analysis that (unlike conventional regression modeling) appropriately adjusts for confounding variables on the causal pathway linking the treatment with the outcome. They discuss the need for marginal structural models in social science research and describe their estimation in detail. Substantively, the authors contribute to the ongoing debate on the effects of incarceration on marriage …

Negative Binomial Regerssion, 2nd Ed, 2nd Print, Errata And Comments, Joseph Hilbe

Joseph M Hilbe

Errata and Comments for 2nd printing of NBR2, 2nd edition. Previous errata from first printing all corrected. Some added and new text as well.

Variation In Rheumatoid Hand And Wrist Surgery Among Medicare Beneficiaries: A Population-Based Cohort Study, Lin Zhong, Kevin C. Chung, Onur Baser, David A. Fox, Huseyin Yuce, Jennifer F. Waljee

Publications and Research

Objective. To examine the rate and variation in rheumatoid arthritis (RA)-related hand and wrist surgery among Medicare (elderly) beneficiaries in the United States, and to identify the patient and provider factors that influence surgical rates.

Methods. Using the 2006–2010 100% Medicare claims data of beneficiaries with RA diagnosis, we examined rates of rheumatoid hand and wrist arthroplasty, arthrodesis, and hand tendon reconstruction in the United States. We used multivariate logistic regression models to examine variation in receipt of surgery by patient and regional characteristics (density of providers, intensity of use of biologic disease-modifying antirheumatic drugs).

Results. Between 2006 and 2010, …

Statistical Methods In Topological Data Analysis For Complex, High-Dimensional Data, Patrick S. Medina, R W. Doerge

Conference on Applied Statistics in Agriculture

The utilization of statistical methods an their applications within the new field of study known as Topological Data Analysis has has tremendous potential for broadening our exploration and understanding of complex, high-dimensional data spaces. This paper provides an introductory overview of the mathematical underpinnings of Topological Data Analysis, the workflow to convert samples of data to topological summary statistics, and some of the statistical methods developed for performing inference on these topological summary statistics. The intention of this non-technical overview is to motivate statisticians who are interested in learning more about the subject.

Best Linear Unbiased Prediction: An Illustration Based On, But Not Limited To, Shelf Life Estimation, Maryna Ptukhina, Walter Stroup

Conference on Applied Statistics in Agriculture

Shelf life estimation procedures, following ICH guidelines, use multiple batch regression with fixed batch effects. This guidance specifically mandates estimates based on at least 3 batches. Technically, the fixed-batch model limits inference to the batches actually observed, whereas ICH requires resulting estimates to apply to all future batches stored under similar conditions. This creates a conflict between the model used and the inference space the model is intended to address. Quinlan, et al. (2013) and Schwenke (2010) studied the small sample behavior of this procedure. Both studies revealed large sampling variation associated with the ICH procedure, producing a substantial proportion …

Shiga Toxin-Producing Escherichia Coli In Meat: A Preliminary Simulation Study On Detection Capabilities For Three Sampling Methods, Julie Couton, David Marx, John Luchaansky, Randall Phebus, Anna Porto-Fett, Nicholas Sevart, Manpreet Singh, Harshavardhan Thippareddi

Conference on Applied Statistics in Agriculture

Contamination by Shiga Toxin-producing Escherichia coli (STEC) is a continuing concern for meat production facility management throughout the United States. Several methods have been used to detect STEC during meat processing, however the excessive experimental cost of determining the optimal method is rarely feasible. The objective of this preliminary simulation study is to determine which sampling method (Cozzini core sampler, core drill shaving, and N-60 surface excision) will better detect STEC at varying levels of contamination present in the meat. 1000 simulated experiments were studied using a binary model for rare occurrences to find the optimal method. We found that …

Differential Methylation Methods In Multi-Context Organisms, Douglas Baumann, Yuqing Su, Iranga Mendis, Gayla R. Olbricht

Conference on Applied Statistics in Agriculture

DNA methylation is an epigenetic modification that has the ability to alter gene expression without any change in the DNA sequence. DNA methylation occurs when a methyl chemical group attaches to cytosine bases on the DNA sequence. In mammals, DNA methylation primarily occurs at CG sites, when a cytosine is followed by a guanine in the DNA sequence. In plants, DNA methylation can also occur in other cytosine sequences, such as when a cytosine is not followed directly by a guanine. Many of the statistical methods that have been developed to estimate methylation levels and test differential methylation in whole-genome …

On Fixed Effects Estimation In Spline-Based Semiparametric Regression For Spatial Data, Guilherme Ludwig, Jun Zhu, Chun-Shu Chen

Conference on Applied Statistics in Agriculture

Spline surfaces are often used to capture spatial variability sources in linear mixed-effects models, without imposing a parametric covariance structure on the random effects. However, including a spline component in a semiparametric model may change the estimated regression coefficients, a problem analogous to spatial confounding in spatially correlated random effects. Our research aims to investigate such effects in spline-based semiparametric regression for spatial data. We discuss estimators' behavior under the traditional spatial linear regression, how the estimates change in spatial confounding-like situations, and how selecting a proper tuning parameter for the spline can help reduce bias.

Small Sample Properties Of The Two Independent Sample Test For Means From Beta Distributions, Edward E. Gbur, Kevin Thompson

Conference on Applied Statistics in Agriculture

Researchers often collect proportion data that cannot be interpreted as arising from a set of Bernoulli trials. Analyses based on the beta distribution may be appropriate for such data. The SAS® GLIMMIX procedure provides a tool for these analyses using a likelihood based approach within the larger context of generalized linear mixed models (GLMM). The small sample behavior of likelihood based tests to compare the means from two independently sampled beta distributions were studied via simulation when the null hypothesis of equal means holds. Two simulation scenarios were defined by equal and unequal sample sizes and equal scale parameters. A …