Applied Statistics Commons^™

Evaluating The Efficacy Of Conditional Analysis Of Variance Under Heterogeneity And Non-Normality, Yan Wang, Thanh Pham, Diep Nguyen, Eun Sook Kim, Yi-Hsin Chen, Jeffrey Kromrey, Zhiyao Yi, Yue Yin

Journal of Modern Applied Statistical Methods

A simulation study was conducted to examine the efficacy of conditional analysis of variance (ANOVA) methods where the initial homogeneity of variance screening leads to the choice between the ANOVA F test and robust ANOVA methods. Type I error control and statistical power were investigated under various conditions.

College Students’ Personality Traits In Relation To Career Readiness, Shelby R. Overacker, Carly E. Kalis, Francesca Coppola

Student Publications

This study examined sixty-one Gettysburg College juniors and seniors (31 males, 30 females) to measure how the Big Five personality traits, and whether a student has Type D characteristics, determines if a student is career ready. We collected data through an in-person survey, with questions about personality traits, ambition, career readiness, and demographics. Regression was used to statistically analyze our first hypothesis. The results found that there is a significant positive association between conscientiousness and career readiness, but there is no significant association between extraversion and career readiness. For the second hypothesis, a mediation model was used. We found that …

Perceptions Of Transactional And Transformational Leaders According To Gender, Quinn I. Igram, Andrew N. Garstka, Lindsay D. Harris

Student Publications

The lack of females occupying leadership positions in the modern workplace has prompted the research of this study. In order to better understand the perceptions that exist regarding successful leadership, this study was conducted with the intention of understanding individual leadership style through the Multifactor Leadership Questionnaire, which measures transactional and transformational leadership styles (Bass and Avolio, 1993). 64 male and female participants, made up of 36 students and 28 individuals in the workforce ages 18-61 with an average age of 31 answered 21 questions to assess their leadership style and 1 to measure who they perceived as a successful …

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books Collection

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling …

Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov

Journal of Humanistic Mathematics

We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic …

Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov

Publications and Research

We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic …

A Preliminary Study Of Smithport Plain Bottle Morphology In The Southern Caddo Area, Robert Z. Selden Jr.

CRHR: Archaeology

This study expands upon a previous analysis of the Clarence H. Webb collection, which resulted in the identification of two discrete shapes used in the manufacture of the base and body of Smithport Plain bottles. The sample includes the Smithport Plain bottles from the Webb collection, and four new bottles: two previously repatriated specimens in the Pohler Collection, and two from the Mitchell site (41BW4) to test whether those specimens align morphologically with the Belcher Mound or Smithport Landing specimens. Results indicate significant allometry and a significant difference in Smithport Plain body and base shapes for bottles produced at the …

Gene × Environment Interaction: What Exactly Are We Talking About?, David S. Moore

Pitzer Faculty Publications and Research

An ambiguity exists in how psychological scientists use the word “interaction.” This word can refer to physical interactions between components that constitute the mechanisms in complex systems, but it can also refer to statistical interactions revealed by General Linear Statistical Models (e.g., Analyses of Variance). Statistical interactions indicate that the nature of the relationship between two variables depends on a third variable, but the discovery of such interactions does not constitute evidence of physical interactions between components in a system. Studies conducted using traditional behavioral genetics methods sometimes reveal statistical interactions between genes and environments, but the presence or absence …

Psychometric Properties Of A Working Memory Span Task, Juan M. Alzate Vanegas

Honors Undergraduate Theses

The intent of this thesis is to examine the psychometric properties of a complex span task (CST) developed to measure working memory capacity (WMC) using measurements obtained from a sample of 68 undergraduate students at the University of Central Florida. The Grocery List Task (GLT) promises several design improvements over traditional CSTs in a prior study about individual differences in WMC and distraction effects on driving performance, and it offers potential benefits for studying WMC as well as the serial-position effect. Currently, the working memory system is composed of domain-general memorial storage processes and information-processing, which involves the use of …

Analysis Of Residential And Auto Break-In Records In Taipei City, Afnan Althoupety, Aishwarya Joy, Juchun Cheng, Priyanka Patil, Tejas Deshpande

Engineering and Technology Management Student Projects

Taipei City is the capital of Taiwan. It has population of 2.7 million living in the city area of 271 km2 (104 mi2). There are totally 12 administrative districts in this city. To maintain the safety of the city, Taipei City Police Bureau has arranged regular patrol routes with focus on the high-risk area where residential and auto break-in occurs. Due to limited police resource, resident neighborhood also organized volunteered patrol teams to enhance the security in residential area. Based on past file record history, the Bureau would like to understand the high-risk districts and time schedule to improve their …

Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger

Theses and Dissertations--Computer Science

Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship …

The Use Of Item Response Theory In Survey Methodology: Application In Seat Belt Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter

Mathematics & Statistics Faculty Publications

Problem: Several approaches to analyze survey data have been proposed in the literature. One method that is not popular in survey research methodology is the use of item response theory (IRT). Since accurate methods to make prediction behaviors are based upon observed data, the design model must overcome computation challenges, but also consideration towards calibration and proficiency estimation. The IRT model deems to be offered those latter options. We review that model and apply it to an observational survey data. We then compare the findings with the more popular weighted logistic regression. Method: Apply IRT model to the observed data …

Campus Climate Sexual Assault Survey (2015) Analysis, Felicia Rosin

Williams Honors College, Honors Research Projects

The issue of sexual assault has garnered widespread attention in recent years, as is evident by the growing number of high-profile cases and mainstream social movements. With this increasingly bright spotlight, it is no surprise that The University of Akron has interest in improving the sexual violence education programs offered to students. In 2015, the university conducted a survey to gather information on the campus climate surrounding sexual assault. This analysis dives into a deeper analysis of the data gathered in an attempt to pinpoint areas that require the university’s attention. The analysis covers topics identified by Dean of Students …

Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry

Theses and Dissertations

The Brisbane Longitudinal Twin Study (BLTS) was being conducted in Australia and was funded by the US National Institute on Drug Abuse (NIDA). Adolescent twins were sampled as a part of this study and surveyed about their substance use as part of the Pathways to Cannabis Use, Abuse and Dependence project. The methods developed in this dissertation were designed for the purpose of analyzing a subset of the Pathways data that includes demographics, cannabis use metrics, personality measures, and imputed genotypes (SNPs) for 493 complete twin pairs (986 subjects.) The primary goal was to determine what combination of SNPs and …

Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation, Ghasem Rekabdar, Rahim Chinipardaz

Journal of Modern Applied Statistical Methods

The quadratic form of non-central normal variables is presented based on a sum of weighted independent non-central chi-square variables. This presentation provides moments of quadratic form. The maximum entropy method is used to estimate the density function because distribution moments of quadratic forms are known. A Euclidean distance is proposed to select an appropriate maximum entropy density function. In order to compare with other methods some numerical examples were evaluated. Also, for discrimination between two groups by the Euclidean distances, we obtained a stochastic representation for the linear discriminant function using the quadratic form. The maximum entropy estimation was an …

Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous

Journal of Modern Applied Statistical Methods

Most reliability studies obtained reliability information by using degradation measurements over time, which contains useful data about the product reliability. Parametric methods like the maximum likelihood (ML) estimator and the ordinary least square (OLS) estimator are used widely to estimate the time-to-failure distribution and its percentiles. In this article, we estimate the time-to-failure distribution and its percentiles by using a semi-parametric estimator that assumes the parametric function to have a half- normal distribution or an exponential distribution. The performance of the semi-parametric estimator is compared via simulation study with the ML and OLS estimators by using the mean square error …

Jmasm 48: The Pearson Product-Moment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The Olkin-Pratt Adjustment (Spss), David A. Walker

Journal of Modern Applied Statistical Methods

This syntax program is intended to provide an application, not readily available, for users in SPSS who are interested in the Pearson product–moment correlation coefficient (r) and r biased adjustment indices such as the Fisher Approximate Unbiased estimator and the Olkin and Pratt adjustment.

Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar

Journal of Modern Applied Statistical Methods

The log logistic model with doubly interval censored data is examined. Three methods of constructing confidence interval estimates for the parameter of the model were compared and discussed. The results of the coverage probability study indicated that the Wald outperformed the likelihood ratio and jackknife inferential procedures.

On Poisson Quasi-Lindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi

Journal of Modern Applied Statistical Methods

This paper proposes a recent version of compound Poisson distributions named the Poisson quasi-Lindley (PQL) distribution by compounding Poisson and quasi-Lindley distributions. Some properties of the distributions are given with estimation and some illustrative examples.

Detection Of Outliers In Univariate Circular Data Using Robust Circular Distance, Ehab A. Mahmood, Sohel Rana, Habshah Midi, Abdul Ghapor Hussin

Journal of Modern Applied Statistical Methods

A robust statistic to detect single and multi-outliers in univariate circular data is proposed. The performance of the proposed statistic was tested by applying it to a simulation study and to three real data sets, and was demonstrated to be robust.

Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson

Journal of Modern Applied Statistical Methods

Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently large-scale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in large-scale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies.

Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç

Journal of Modern Applied Statistical Methods

The main purpose of this study is to review calculation algorithms for some of the most common non-parametric and omnibus tests for normality, and to provide them as a compiled MATLAB function. All tests are coded to provide p-values for those normality tests, and the proposed function gives the results as an output table.

The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

A series of simulation studies are reported that investigated the impact of a skewed predictor(s) on the Type I error rate and power of the Wald test in a logistic regression model. Five simulations were conducted for three different regression models. A detailed description of the impact of skewed cell predictor probabilities and sample size provide guidelines for practitioners wherein to expect the greatest problems.

Jmasm 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

A web-based Shiny application written in R statistical language was developed and deployed online to calculate a new two dependent samples maximum test as presented in Maggio and Sawilowsky (2014b). The maximum test allows researchers to conduct both the dependent samples t-test and Wilcoxon signed-ranks tests on same data without raising concerns associated with Type I error inflation and choice of statistical tests (Maggio and Sawilowsky, 2014a). The maximum test in R statistical language provides a friendly user interface.

Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas), Isaac Li, Yi-Hsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey

Journal of Modern Applied Statistical Methods

Variance homogeneity (HOV) is a critical assumption for ANOVA whose violation may lead to perturbations in Type I error rates. Minimal consensus exists on selecting an appropriate test. This SAS macro implements 14 different HOV approaches in one-way ANOVA. Examples are given and practical issues discussed.

A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai

Journal of Modern Applied Statistical Methods

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Front Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Vol. 16, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié

Journal of Modern Applied Statistical Methods

Of the three kinds of two-mean comparisons which judge a test statistic against a critical value taken from a Student t-distribution, one – the repeated measures or dependent-means application – is distinctive because it is meant to assess the value of a parameter which is not part of the natural order. This absence forces a choice between two interpretations of a significant test result and the meaning of the test hypothesis. The parallel universe view advances a conditional, backward-looking conclusion. The more practical proven future interpretation is a non-conditional proposition about what will happen if an intervention is (now) applied …

Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar

Journal of Modern Applied Statistical Methods

The univariate time series models, in the case of unit root hypothesis, are more biased towards the acceptance of the Unit Root Hypothesis especially in a short time span. However, the panel data time series model is more appropriate in such situation. The Bayesian analysis of unit root testing for a panel data time series model is considered. An autoregressive panel data AR(1) model with linear time trend and augmentation term has been considered and derived the posterior odds ratio for testing the presence of unit root hypothesis under appropriate prior assumptions. A simulation study and real data analysis are …