Physical Sciences and Mathematics Commons^™

Assessing Content Validity Through Correlation And Relevance Tools A Bayesian Randomized Equivalence Experiment, Byron Gajewski, Diane Boyle, Marjorie Bott, Larry Price, Jamie Leopold, Nancy Dunton

Diane Kay Boyle PhD, RN, FAAN

Content validity elicits expert opinion regarding items of a psychometric instrument. Expert opinion can be elicited in many forms: for example, how essential an item is or its relevancy to a domain. This study developed an alternative tool that elicits expert opinion regarding correlations between each item and its respective domain. With 109 Registered Nurse (RN) site coordinators from National Database of Nursing Quality Indicators, we implemented a randomized Bayesian equivalence trial with coordinators completing ‘‘relevance’’ or ‘‘correlation’’ content tools regarding the RN Job Enjoyment Scale. We confirmed our hypothesis that the two tools would result in equivalent content information. …

A Comparative Analysis Of Decision Trees Vis-À-Vis Other Computational Data Mining Techniques In Automotive Insurance Fraud Detection, Adrian Gepp, Kuldeep Kumar, J Holton Wilson, Sukanto Bhattacharya

Kuldeep Kumar

No abstract provided.

Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans

Lonnie K. Stevans

The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …

Paradoxical Results Of Adaptive False Discovery Rate Procedures In Neuroimaging Studies, Philip T. Reiss, Armin Schwartzman, Feihan Lu, Lei Huang, Erika Proal

Philip T. Reiss

Adaptive false discovery rate (FDR) procedures, which offer greater power than the original FDR procedure of Benjamini and Hochberg, are often applied to statistical maps of the brain. When a large proportion of the null hypotheses are false, as in the case of widespread effects such as cortical thinning throughout much of the brain, adaptive FDR methods can surprisingly reject more null hypotheses than not accounting for multiple testing at all—i.e., using uncorrected p-values. A straightforward mathematical argument is presented to explain why this can occur with the q-value method of Storey and colleagues, and a simulation study shows that …

Retailing Nears Holy Grail In 'Big Data', Jennifer Priestley

Jennifer L. Priestley

(First paragraph) Yesterday I was online looking for a red, cotton wrap skirt, size 6 (OK, maybe size 8). After viewing several different retail sites, clicking through countless options, I found the perfect skirt. But I had to “abandon” my cart to take care of a minor household crisis. When I went back online, it seemed as if every ad included size 6 women, wearing red wrap skirts. Even more interesting, most came with an incentive for free shipping or 10 percent off.

Prediction Of Radiation Pneumonitis By Dose-Volume Histogram Parameters In Lung Cancer--A Systematic Review, George Rodrigues, Michael Lock, David D'Souza, Edward Yu, Jake Van Dyk

Michael Lock

BACKGROUND AND PURPOSE: To perform a systematic review of the predictive ability of various dose-volume histogram (DVH) parameters (V(dose), mean lung dose (MLD), and normal tissue complication probability (NTCP)) in the incidence of radiation pneumonitis (RP) caused by external-beam radiation therapy.

METHODS AND MATERIALS: Studies assessing the relationship between CT-based DVH reduction parameters and RP rate in radically treated lung cancer were eligible for the review. Synonyms for RP, lung cancer, DVH and its associated parameters (NTCP, V(20), V(30), MLD) were combined in a search strategy involving electronic databases, secondary reference searching, and consultation with experts. Individual or group data …

Technology Assessment Of Automated Atlas Based Segmentation In Prostate Bed Contouring, Jeremiah Hwee, Alexander Louie, Stewart Gaede, Glenn Bauman, David D'Souza, Tracy Sexton, Michael Lock, Belal Ahmad, George Rodrigues

Michael Lock

BACKGROUND: Prostate bed (PB) contouring is time consuming and associated with inter-observer variability. We evaluated an automated atlas-based segmentation (AABS) engine in its potential to reduce contouring time and inter-observer variability.

METHODS: An atlas builder (AB) manually contoured the prostate bed, rectum, left femoral head (LFH), right femoral head (RFH), bladder, and penile bulb of 75 post-prostatectomy cases to create an atlas according to the recent RTOG guidelines. 5 other Radiation Oncologists (RO) and the AABS contoured 5 new cases. A STAPLE contour for each of the 5 patients was generated. All contours were anonymized and sent back to the …

Big Data Education: 3 Steps Universities Must Take, Jennifer Priestley

Jennifer L. Priestley

By now, we all know that the "sexiest job of the 21st century" is the data scientist. A scan of articles and blogs describing data scientists and their raw material -- big data -- reveals several "sexy" themes. First, data is ubiquitous, big and coming at us with increasing velocity. Second, traditional tools that have been used to extract and analyze 20th century data don't work with big data. Third, incredibly few people have the skills necessary to translate this tsunami of data into meaningful information -- making them the hotshots in the job market.

Adaptive Matching In Randomized Trials And Observational Studies, Mark J. Van Der Laan, Laura Balzer, Maya L. Petersen

Laura B. Balzer

In many randomized and observational studies the allocation of treatment among a sample of n independent and identically distributed units is a function of the covariates of all sampled units. As a result, the treatment labels among the units are possibly dependent, complicating estimation and posing challenges for statistical inference. For example, cluster randomized trials frequently sample communities from some target population, construct matched pairs of communities from those included in the sample based on some metric of similarity in baseline community characteristics, and then randomly allocate a treatment and a control intervention within each matched pair. In this case, …

Obtaining Critical Values For Test Of Markov Regime Switching, Douglas G. Steigerwald, Valerie Bostwick

Douglas G. Steigerwald

For Markov regime-switching models, testing for the possible presence of more than one regime requires the use of a non-standard test statistic. Carter and Steigerwald (forthcoming, Journal of Econometric Methods) derive in detail the analytic steps needed to implement the test ofMarkov regime-switching proposed by Cho and White (2007, Econometrica). We summarize the implementation steps and address the computational issues that arise. A new command to compute regime-switching critical values, rscv, is introduced and presented in the context of empirical research.

Let's Come Together On Data Science, Jennifer Priestley

Jennifer L. Priestley

We've all read the articles and blogs. Many of us have experienced the issues directly -- the demand for deep analytical skills is outpacing the supply. As evidence of this, in a period of economic slowdown, where we read that 50 percent of college graduates can't get a job, college graduates with degrees remotely aligned with applied analytics have multiple offers in advance of graduation. Academic training in applied (versus theoretical) statistics is helpful -- and mitigates some of this talent gap at the entry level. Nonetheless, we all know it's insufficient to meet the growing demand for what we …

An Integrated Education Planning Model For Strategic Decisions Using System Dynamics, Mridula Sahay, Kuldeep Kumar

Kuldeep Kumar

Extract

Education has great social significance. No country can develop without providing quality education to their country man. As it plays a major role in improving economic opportunities for people and enhancing their quality of life by building capabilities, skill levels and providing more productive employment.

This paper aims to provide an integrated model for education planning combining all the levels of education (primary and junior school level, high school level, degree and PG level, professional level) for strategic decision using system dynamics methodology for educational growth.

Role Of Teaching Ethics In Higher Education, Sanjay Mishra, Kuldeep Kumar

Kuldeep Kumar

ExtractIn view of the increasing number of frauds, scandals and other malpractices being committed in various disciplines all over the world teaching of ethical values has become important to all students especially professional students. Targeting this in view many universities in Australia and the USA have made teaching of ethics as compulsory subject at the under graduate level. India is also following this lead and awareness of teaching ethics as a subject is gaining momentum. In this paper we have outlined how ethics can be taught as a compulsory subject as well as how we can incorporate teaching of ethical …

Disparities In Globalization Of The World Economies, Sudhanshu K. Mishra, Binod Kumar

Sudhanshu K Mishra

This paper constructs composite indices of globalization of 131 countries spread over the five continents and classified into World-I, World-II and World-III countries. KOF, the Business Cycle Research Institute in the Swiss Federal Institute of Technology, Zurich is the source of data used in this study. The Composite Indices of Globalization have been computed by Pena’s method, which attributes the most desirable properties to the indices so constructed. On the basis of these indices, the paper investigates into the trends of globalization and disparities in globalization for a period of 11 years (1999-2009). Disparities have been obtained as the Gini’s …

Regional Specialization: Measurement & Application, Zheng Lu

Zheng Lu (Chinese: 路征)

Various measure methods for regional specialization and evolution of China's regional specialization are introduced in this presentation.

A Statistical Model To Forecast Short-Term Atlantic Hurricane Intensity, Kevin Law, Jay Hobgood

Kevin Law

An alternative 24-h statistical hurricane intensity model is presented and verified for 13 hurricanes during the 2004–05 seasons. The model uses a new method involving a discriminant function analysis (DFA) to select from a collection of multiple regression equations. These equations were developed to predict the future 24-h wind speed increase and the 24-h pressure drop that were constructed from a dataset of 103 hurricanes from 1988 to 2003 that utilized 25 predictors of rapid intensification. The accuracy of the 24-h wind speed increase models was tested and compared with the official National Hurricane Center (NHC) 24-h intensity forecasts, which …

Big Data And The Future, Sherri Rose

Sherri Rose

No abstract provided.

Function-On-Scalar Regression With The Refund Package, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Combined Eeg And Eye Tracking In Sports Skills Training And Performance Analysis, Keith Barfoot, Matthew Casey, Andrew J. Callaway

Andrew J Callaway

No abstract provided.

Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter

Russell T Warne

This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson’s r (47.8%), χ2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach’s alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.

A Logistic L-Moment-Based Analog For The Tukey G-H, G, H, And H-H System Of Distributions, Todd C. Headrick, Mohan D. Pant

Mohan Dev Pant

This paper introduces a standard logistic L-moment-based system of distributions. The proposed system is an analog to the standard normal conventional moment-based Tukey g-h, g, h, and h-h system of distributions. The system also consists of four classes of distributions and is referred to as (i) asymmetric γ-κ, (ii) log-logistic γ, (iii) symmetric κ, and (iv) asymmetric κL-κR. The system can be used in a variety of settings such as simulation or modeling events—most notably when heavy-tailed distributions are of interest. A procedure is also described for simulating γ-κ, γ, κ, and κL-κR distributions with specified L-moments and L-correlations. The …

Computing Highly Accurate Or Exact P-Values Using Importance Sampling, Chris Lloyd

Chris J. Lloyd

Especially for discrete data, standard first order P-values can suffer from poor accuracy, even for quite large sample sizes. Moreover, different test statistics can give practically different results. There are several approaches to computing P-values which do not suffer these defects, such as parametric bootstrap P-values or the partially maximised P-values of Berger and Boos (1994).

Both these methods require computing the exact tail probability of the approximate P-value as a function of the nuisance parameter/s, known as the significance profile. For most practical problems, this is not computationally feasible. I develop an importance sampling approach to this problem. A …

Estimating The Impact Of Community-Level Interventions: The Search Trial And Hiv Prevention In Sub-Saharan Africa, Laura Balzer, Maya Petersen, Joshua Schwab, Mark Van Der Laan

Laura B. Balzer

Evaluation of community level interventions to prevent HIV infection presents significant methodological challenges. Even when it is feasible to randomly assign a treatment versus control level of the intervention to each community in a sample, measurement of incident HIV infection remains difficult. In this talk we describe an experimental design developed for the SEARCH Trial, a large community randomized trial that will evaluate the impact of expanded treatment on incident HIV and other outcomes. Regular community-wide testing campaigns are conducted and a random sample of community members who fail to attend a campaign are tracked. The data generated by this …

Construction Of Pena’S Dp2-Based Ordinal Synthetic Indicator When Partial Indicators Are Rank Scores, Sudhanshu K. Mishra

Sudhanshu K Mishra

The present study devises a computational scheme (and develops a FORTRAN 77 computer program) that may be appropriate to construct Pena’s DP2 (ordinal) synthetic indicator (Z) from the partial indicators (X) all of which are ordinal (ranking scores). An attempt has also been made to empirically apply the method (and the computer program) to obtain an ordinal synthetic indicator from a given ordinal data set.

Why Match In Individually And Cluster Randomized Trials?, Laura B. Balzer, Maya L. Petersen, Mark J. Van Der Laan

Laura B. Balzer

The decision to match individuals or clusters in randomized trials is motivated by both practical and statistical concerns. Matching protects against chance imbalances in baseline covariate distributions and is thought to improve study credibility. Matching is also implemented to increase study power. This article compares the asymptotic efficiency of the pair-matched design, where units are matched on baseline covariates and the treatment randomized within pairs, to the independent design, where units are randomly paired and the treatment randomized within pairs. We focus on estimating the average treatment effect and use the efficient influence curve to understand the information provided by …

Detecting Clustered Chem/Bio Signals In Noisy Sensor Feeds Using Adaptive Fusion, Randy Paffenroth, Scott Lundberg, Chris Calderon

Randy C. Paffenroth

Chemical and biological monitoring systems are faced with the challenge of detecting weak signals from contam- inants of interest while at the same time maintaining extremely low false alarm rates. We present methods to control the number of false alarms while maintaining power to detect; evaluating these methods on a fixed sensor grid. Contaminants are detected using signals produced from underlying sensor-specific detection algorithms. By learning from past data, an adaptive background model is constructed and used with a multi-hypothesis testing method to control the false alarm rate. Detection methods for chemical/biological releases often depend on specific models for release …

Distributed Pattern Detection In Cyber Networks, Randy Paffenroth, Philip Du Toit, Louis Scharf, Anura Jayasumana, Vidarshana Banadara, Ryan Nong

Randy C. Paffenroth

In this paper we describe an approach for the detection and classication of weak, distributed patterns in sensor networks. Of course, before one can begin development of a pattern detection algorithm, one must rst dene the term "pattern", which by nature is a broad and inclusive term. One of the key aspects of our work is a denition of pattern that has already proven eective in detecting anomalies in real world data. While designing detection algorithms for all classes of patterns in all types of networks sounds appealing, this approach would almost certainly require heuristic methods and only cursory statements …

Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne

Russell T Warne

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.

Why Match In Individually And Cluster Randomized Trials?, Laura Balzer, Maya Petersen, Mark Van Der Laan

Laura B. Balzer

The decision to match individuals or clusters in randomized trials is motivated by both practical and statistical concerns. Matching protects against chance imbalances in baseline covariate distributions and is thereby thought to improve study credibility. Matching is also implemented to increase study power. Analogue to Rose and van der Laan (2009), this article investigates the asymptotic efficiency of pair-matching individuals or clusters relative to not matching in randomized trials. We focus on estimating the average treatment effect. We use the efficient influence curve to understand the information provided by each design for estimation of the target causal parameter. Our approach …

Smoothness Selection For Penalized Quantile Regression Splines, Philip T. Reiss, Lei Huang

Philip T. Reiss

Modern data-rich analyses may call for fitting a large number of nonparametric quantile regressions. For example, growth charts may be constructed for each of a collection of variables, to identify those for which individuals with a disorder tend to fall in the tails of their age-specific distribution; such variables might serve as developmental biomarkers. When such analyses are carried out by penalized spline smoothing, reliable automatic selection of the smoothing parameter is particularly important. We show that two popular methods for smoothness selection may tend to overfit when estimating extreme quantiles as a smooth function of a predictor such as …