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Full-Text Articles in Applied Statistics

Bivariate Analogs Of The Wilcoxon–Mann–Whitney Test And The Patel–Hoel Method For Interactions, Rand Wilcox Feb 2020

Bivariate Analogs Of The Wilcoxon–Mann–Whitney Test And The Patel–Hoel Method For Interactions, Rand Wilcox

Journal of Modern Applied Statistical Methods

A fundamental way of characterizing how two independent compares compare is in terms of the probability that a randomly sampled observation from the first group is less than a randomly sampled observation from the second group. The paper suggests a bivariate analog and investigates methods for computing confidence intervals. An interaction for a two-by-two design is investigated as well.


Assessing The Accuracy Of Approximate Confidence Intervals Proposed For The Mean Of Poisson Distribution, Alireza Shirvani, Malek Fathizadeh Feb 2020

Assessing The Accuracy Of Approximate Confidence Intervals Proposed For The Mean Of Poisson Distribution, Alireza Shirvani, Malek Fathizadeh

Journal of Modern Applied Statistical Methods

The Poisson distribution is applied as an appropriate standard model to analyze count data. Because this distribution is known as a discrete distribution, representation of accurate confidence intervals for its distribution mean is extremely difficult. Approximate confidence intervals were presented for the Poisson distribution mean. The purpose of this study is to simultaneously compare several confidence intervals presented, according to the average coverage probability and accurate confidence coefficient and the average confidence interval length criteria.


Analytical Closed-Form Solution For General Factor With Many Variables, Stan Lipovetsky, Vladimir Manewitsch Feb 2020

Analytical Closed-Form Solution For General Factor With Many Variables, Stan Lipovetsky, Vladimir Manewitsch

Journal of Modern Applied Statistical Methods

The factor analytic triad method of one-factor solution gives the explicit analytical form for a common latent factor built by three variables. The current work considers analytical presentation of a general latent factor constructed in a closed-form solution for multivariate case. The results can be supportive to theoretical description and practical application of latent variable modeling, especially for big data because the analytical closed-form solution is not prone to data dimensionality.


Regression Modeling And Prediction By Individual Observations Versus Frequency, Stan Lipovetsky Feb 2020

Regression Modeling And Prediction By Individual Observations Versus Frequency, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

A regression model built by a dataset could sometimes demonstrate a low quality of fit and poor predictions of individual observations. However, using the frequencies of possible combinations of the predictors and the outcome, the same models with the same parameters may yield a high quality of fit and precise predictions for the frequencies of the outcome occurrence. Linear and logistical regressions are used to make an explicit exposition of the results of regression modeling and prediction.


The Author’S Reflections On No B.S. (Bad Stats): Black People Need People Who Believe In Black People Enough Not To Believe Every Bad Thing They Hear About Black People, Ivory A. Toldson Jan 2020

The Author’S Reflections On No B.S. (Bad Stats): Black People Need People Who Believe In Black People Enough Not To Believe Every Bad Thing They Hear About Black People, Ivory A. Toldson

Numeracy

Toldson, Ivory. A. 2019. No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear About Black People (Boston, MA: Brill-Sense) 194 pp. ISBN 978-9004397026.

This essay provides an introduction to No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear About Black People. In the essay, the author discusses how cynical views about the educational potential of Black children motivated him to write a book that challenges negative statistics. The essay also outlines the harmful …


An Analysis Of The Success Of Farmers Markets In Kentucky Using Logistic Regression And Support Vector Machines, Jeron Russell Jan 2020

An Analysis Of The Success Of Farmers Markets In Kentucky Using Logistic Regression And Support Vector Machines, Jeron Russell

Mahurin Honors College Capstone Experience/Thesis Projects

The purpose of this research is to look at the relationship that market-specific, economic, and demographic variables have with the success of farmers markets in Kentucky. It additionally seeks to build a tool for predicting farmers market success that could be used by policy makers to aid in decision-making processes concerning farmers markets. Logistic regression and Support Vector Machines (SVMs) are used on data acquired from the Kentucky Department of Agriculture and the American Community Survey in order to analyze the data in a traditional statistical approach as well as a machine learning approach. The results included an SVM model …


Three Essays On Health Economics And Policy Evaluation, Shishir Shakya Jan 2020

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …


Mass Grave Localization Prediction With Geographical Information Systems In Guatemala And Future Impacts, Perla Santillan Jan 2020

Mass Grave Localization Prediction With Geographical Information Systems In Guatemala And Future Impacts, Perla Santillan

Master of Science in Forensic Science Directed Research Projects

Conducting physical searches for mass grave locations based on anecdotal evidence is a time consuming and resource intensive endeavor in circumstances that often pose a threat to personal safety. The development of tools and procedures to speed such searches can greatly reduce the risk involved, increase the number of individuals whose remains are recovered and identified; and, more importantly, reunite these remains with their loved ones to provide them with a proper burial. Geographic information systems (GIS) software, which can analyze and manipulate the spatial characteristics of known mass grave data, represents a powerful tool that can be used to …


Phenotype Extraction: Estimation And Biometrical Genetic Analysis Of Individual Dynamics, Kevin L. Mckee Jan 2020

Phenotype Extraction: Estimation And Biometrical Genetic Analysis Of Individual Dynamics, Kevin L. Mckee

Theses and Dissertations

Within-person data can exhibit a virtually limitless variety of statistical patterns, but it can be difficult to distinguish meaningful features from statistical artifacts. Studies of complex traits have previously used genetic signals like twin-based heritability to distinguish between the two. This dissertation is a collection of studies applying state-space modeling to conceptualize and estimate novel phenotypic constructs for use in psychiatric research and further biometrical genetic analysis. The aims are to: (1) relate control theoretic concepts to health-related phenotypes; (2) design statistical models that formally define those phenotypes; (3) estimate individual phenotypic values from time series data; (4) consider hierarchical …


Modelling Interactions Among Offenders: A Latent Space Approach For Interdependent Ego-Networks, Isabella Gollini, Alberto Caimo, Paolo Campana Jan 2020

Modelling Interactions Among Offenders: A Latent Space Approach For Interdependent Ego-Networks, Isabella Gollini, Alberto Caimo, Paolo Campana

Articles

Illegal markets are notoriously difficult to study. Police data offer an increasingly exploited source of evidence. However, their secondary nature poses challenges for researchers. A key issue is that researchers often have to deal with two sets of actors: targeted and non-targeted. This work develops a latent space model for interdependent ego-networks purposely created to deal with the targeted nature of police evidence. By treating targeted offenders as egos and their contacts as alters, the model (a) leverages on the full information available and (b) mirrors the specificity of the data collection strategy. The paper then applies this approach to …


Personalized Detection Of Anxiety Provoking News Events Using Semantic Network Analysis, Jacquelyn Cheun Phd, Luay Dajani, Quentin B. Thomas Dec 2019

Personalized Detection Of Anxiety Provoking News Events Using Semantic Network Analysis, Jacquelyn Cheun Phd, Luay Dajani, Quentin B. Thomas

SMU Data Science Review

In the age of hyper-connectivity, 24/7 news cycles, and instant news alerts via social media, mental health researchers don't have a way to automatically detect news content which is associated with triggering anxiety or depression in mental health patients. Using the Associated Press news wire, a semantic network was built with 1,056 news articles containing over 500,000 connections across multiple topics to provide a personalized algorithm which detects problematic news content for a given reader. We make use of Semantic Network Analysis to surface the relationship between news article text and anxiety in readers who struggle with mental health disorders. …


Communications And Methodologies In Crime Geography: Contemporary Approaches To Disseminating Criminal Incidence And Research, Mitchell Ogden Dec 2019

Communications And Methodologies In Crime Geography: Contemporary Approaches To Disseminating Criminal Incidence And Research, Mitchell Ogden

Electronic Theses and Dissertations

Many tools exist to assist law enforcement agencies in mitigating criminal activity. For centuries, academics used statistics in the study of crime and criminals, and more recently, police departments make use of spatial statistics and geographic information systems in that pursuit. Clustering and hot spot methods of analysis are popular in this application for their relative simplicity of interpretation and ease of process. With recent advancements in geospatial technology, it is easier than ever to publicly share data through visual communication tools like web applications and dashboards. Sharing data and results of analyses boosts transparency and the public image of …


Economic Design Of Acceptance Sampling Plans For Truncated Life Tests Using Three-Parameter Lindley Distribution, Amer Ibrahim Al-Omari, Enrico Ciavolino, Amjad D. Al-Nasser Nov 2019

Economic Design Of Acceptance Sampling Plans For Truncated Life Tests Using Three-Parameter Lindley Distribution, Amer Ibrahim Al-Omari, Enrico Ciavolino, Amjad D. Al-Nasser

Journal of Modern Applied Statistical Methods

A single acceptance sampling plan for the three-parameter Lindley distribution under a truncated life test is developed. For various consumer’s confidence levels, acceptance numbers, and values of the ratio of the experimental time to the specified average lifetime, the minimum sample size important to assert a certain average lifetime are calculated. The operating characteristic (OC) function values as well as the associated producer’s risks are also provided. A numerical example is presented to illustrate the suggested acceptance sampling plans.


Utilization Of Statistics For Provision Of Business Information: Implementation Of Α-Sutte Indicator On Provision Of Stock Movement Prediction Information, Nuning Kurniasih, Ansari Saleh Ahmar, Nanik Kurniawati Sep 2019

Utilization Of Statistics For Provision Of Business Information: Implementation Of Α-Sutte Indicator On Provision Of Stock Movement Prediction Information, Nuning Kurniasih, Ansari Saleh Ahmar, Nanik Kurniawati

Library Philosophy and Practice (e-journal)

The Current information services are dealing with big data that is freely accessible. Companies providing information services and products need to develop creativity and innovation to maintain their existence. In this paper, we offer that information specialist can add value to information. The added value is given through an analysis of information that is relevant to user needs. The Research and Development Method can be used to develop a framework for service information products and services, and bridge the gap between the theories studied in higher education and the needs of the industry. α-Sutte Indicator can be used to predict …


The Estimation Of Missing Values In Rectangular Lattice Designs, Emmanuel Ogochukwu Ossai, Abimibola Victoria Oladugba Sep 2019

The Estimation Of Missing Values In Rectangular Lattice Designs, Emmanuel Ogochukwu Ossai, Abimibola Victoria Oladugba

Journal of Modern Applied Statistical Methods

Algebraic expressions for estimating missing data when one or more observation(s) are missing in Rectangular lattice designs with repetition were derived using the method of minimizing the residual sum of squares. Results showed that the estimated value(s) were significantly approximate to that of the actual value(s).


Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir Aug 2019

Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir

Theses and Dissertations

This thesis conducts Value at Risk (VaR) and Expected Shortfall (ES) estimation using GARCH modeling and Bayesian Model Averaging (BMA). BMA considers multiple models weighted by some information criterion. Through BMA, this thesis finds that VaR and ES estimates can be improved through enhanced modeling of the data generation process.


A Randomized Controlled Trial: Attachment-Based Family And Nondirective Supportive Treatments For Youth Who Are Suicidal, Guy S. Diamond, Roger R. Kobak, E. Stephanie Krauthamer Ewing, Suzanne A. Levy, Joanna L. Herres, Jody M. Russon, Robert J. Gallop Jul 2019

A Randomized Controlled Trial: Attachment-Based Family And Nondirective Supportive Treatments For Youth Who Are Suicidal, Guy S. Diamond, Roger R. Kobak, E. Stephanie Krauthamer Ewing, Suzanne A. Levy, Joanna L. Herres, Jody M. Russon, Robert J. Gallop

Mathematics Faculty Publications

Objective: To evaluate the efficacy of attachment-based family therapy (ABFT) compared with a family-enhanced nondirective supportive therapy (FE-NST) for decreasing adolescents’ suicide ideation and depressive symptoms. Method: A randomized controlled trial of 129 adolescents who are suicidal ages 12- to 18-years-old (49% were African American) were randomized to ABFT (n ¼ 66) or FE-NST (n ¼ 63) for 16 weeks of treatment. Assessments occurred at baseline and 4, 8, 12, and 16 weeks. Trajectory of change and clinical recovery were calculated for suicidal ideation and depressive symptoms. Results: There was no significant between-group difference in the rate of change in …


Measure Of Departure From Marginal Average Point-Symmetry For Two-Way Contingency Tables, Kiyotaka Iki, Sadao Tomizawa Jun 2019

Measure Of Departure From Marginal Average Point-Symmetry For Two-Way Contingency Tables, Kiyotaka Iki, Sadao Tomizawa

Journal of Modern Applied Statistical Methods

For the analysis of two-way contingency tables with ordered categories, Yamamoto, Tahata, Suzuki, and Tomizawa (2011) considered a measure to represent the degree of departure from marginal point-symmetry. The maximum value of the measure cannot distinguish two kinds of marginal complete asymmetry with respect to the midpoint. A measure is proposed which can distinguish two kinds of marginal asymmetry with respect to the midpoint. It also gives large-sample confidence interval for the proposed measure.


The Impact Of Equating On Detection Of Treatment Effects, Youn-Jeng Choi, Seohyun Kim, Allan S. Cohen, Zhenqiu Lu Jun 2019

The Impact Of Equating On Detection Of Treatment Effects, Youn-Jeng Choi, Seohyun Kim, Allan S. Cohen, Zhenqiu Lu

Journal of Modern Applied Statistical Methods

Equating makes it possible to compare performances on different forms of a test. Three different equating methods (baseline selection, subgroup, and subscore equating) using common-item item response theory equating were examined for their impact on detection of treatment effects in multilevel models.


The Long-Run Effects Of Tropical Cyclones On Infant Mortality, Isabel Miranda May 2019

The Long-Run Effects Of Tropical Cyclones On Infant Mortality, Isabel Miranda

Master's Theses

In the United States alone, each tropical cyclone causes an average of $14.6 billion worth of damages. In addition to the destruction of physical infrastructure, natural disasters also negatively impact human capital formation. These losses are often more difficult to observe, and therefore, are over looked when quantifying the true costs of natural disasters. One particular effect is an increase in infant mortality rates, an important indicator of a country’s general socioeconomic level. This paper utilizes a model created by Anttila-Hughes and Hsiang, that takes advantage of annual variation in tropical cyclones using annual spatial average maximum wind speeds and …


Upper Record Values From Extended Exponential Distribution, Devendra Kumar, Sanku Dey May 2019

Upper Record Values From Extended Exponential Distribution, Devendra Kumar, Sanku Dey

Journal of Modern Applied Statistical Methods

Some recurrence relations are established for the single and product moments of upper record values for the extended exponential distribution by Nadarajah and Haghighi (2011) as an alternative to the gamma, Weibull, and the exponentiated exponential distributions. Recurrence relations for negative moments and quotient moments of upper record values are also obtained. Using relations of single moments and product moments, means, variances, and covariances of upper record values from samples of sizes up to 10 are tabulated for various values of the shape parameter and scale parameter. A characterization of this distribution based on conditional moments of record …


What Makes A Good Research Consultant?, Justin Harding, Samantha Estrada, Michael Floren May 2019

What Makes A Good Research Consultant?, Justin Harding, Samantha Estrada, Michael Floren

The Qualitative Report

Statistical and research consulting is defined as the collaboration of a statistician or methodologist with another professional for devising solutions to research problems. An in-depth, interview qualitative approach was taken to answer the research question of what makes a good research consultant. The authors interviewed four faculty members in the field of statistics and research methods and two experienced graduate student consultants. In-depth, face-to-face interviews revealed common themes regarding consultancy skills, resourcefulness, communication and interpersonal skills. The participants discussed how to improve consulting sessions and deal with clients with different statistics levels and backgrounds. Participants felt there was no difference …


Advanced Statistics In Arkansas Sports Reporting, Andrew Lee Epperson May 2019

Advanced Statistics In Arkansas Sports Reporting, Andrew Lee Epperson

Graduate Theses and Dissertations

This study seeks to analyze how Arkansas’ sports journalists are adapting to the recent surge in available advanced statistics that are being used by certain national news organizations. Using in-depth qualitative research that includes in-depth interviews with a number of individuals in the print, broadcast, and athletics side of sports coverage, we discover how journalists and coaches use these next-generation analytics, what they fundamentally mean for the evolution of each respective path, and why so few Arkansas reporters and writers use them at the time of this paper’s defense. We see how budgets and deadlines restrict the use of these …


The Andersen Likelihood Ratio Test With A Random Split Criterion Lacks Power, Georg Krammer Apr 2019

The Andersen Likelihood Ratio Test With A Random Split Criterion Lacks Power, Georg Krammer

Journal of Modern Applied Statistical Methods

The Andersen LRT uses sample characteristics as split criteria to evaluate Rasch model fit, or theory driven hypothesis testing for a test. The power and Type I error of a random split criterion was evaluated with a simulation study. Results consistently show a random split criterion lacks power.


Weighted Version Of Generalized Inverse Weibull Distribution, Sofi Mudiasir, S. P. Ahmad Apr 2019

Weighted Version Of Generalized Inverse Weibull Distribution, Sofi Mudiasir, S. P. Ahmad

Journal of Modern Applied Statistical Methods

Weighted distributions are used in many fields, such as medicine, ecology, and reliability. A weighted version of the generalized inverse Weibull distribution, known as weighted generalized inverse Weibull distribution (WGIWD), is proposed. Basic properties including mode, moments, moment generating function, skewness, kurtosis, and Shannon’s entropy are studied. The usefulness of the new model was demonstrated by applying it to a real-life data set. The WGIWD fits better than its submodels, such as length biased generalized inverse Weibull (LGIW), generalized inverse Weibull (GIW), inverse Weibull (IW) and inverse exponential (IE) distributions.


Calibration Of Measurements, Edward Kroc, Bruno D. Zumbo Apr 2019

Calibration Of Measurements, Edward Kroc, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

Traditional notions of measurement error typically rely on a strong mean-zero assumption on the expectation of the errors conditional on an unobservable “true score” (classical measurement error) or on the data themselves (Berkson measurement error). Weakly calibrated measurements for an unobservable true quantity are defined based on a weaker mean-zero assumption, giving rise to a measurement model of differential error. Applications show it retains many attractive features of estimation and inference when performing a naive data analysis (i.e. when performing an analysis on the error-prone measurements themselves), and other interesting properties not present in the classical or Berkson cases. Applied …


Estimation Of Mean With Two-Parameter Ratio-Product-Ratio Estimator In Double Sampling Using Ancillary Information Under Non-Response, Surya K. Pal, Housila P. Singh Apr 2019

Estimation Of Mean With Two-Parameter Ratio-Product-Ratio Estimator In Double Sampling Using Ancillary Information Under Non-Response, Surya K. Pal, Housila P. Singh

Journal of Modern Applied Statistical Methods

Ratio-product-ratio estimators with two parameters in double sampling under non-response are considered along with their properties. Practical conditions are obtained in which the suggested estimators are more proficient than other existing estimators. An example is given.


Efficient Class Of Estimators For Finite Population Mean Using Auxiliary Information In Two-Occasion Successive Sampling, G. N. Singh, Mohd Khalid Apr 2019

Efficient Class Of Estimators For Finite Population Mean Using Auxiliary Information In Two-Occasion Successive Sampling, G. N. Singh, Mohd Khalid

Journal of Modern Applied Statistical Methods

In the case of sampling on two occasions, a class of estimators is considered which uses information on the first occasion as well as the second occasion in order to estimate the population means on the current (second) occasion. The usefulness of auxiliary information in enhancing the efficiency of this estimation is examined through the class of proposed estimators. Some properties of the class of estimators and a strategy of optimum replacement are discussed. The proposed class of estimators were empirically compared with the sample mean estimator in the case of no matching. The established optimum estimator, which is a …


Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan Apr 2019

Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan

Civil & Environmental Engineering Theses & Dissertations

One of the most fundamental tasks when it comes to analyzing data using statistical methods is to understand the relationship between the explanatory variables and the outcome. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. In this dissertation, we define ‘misclassification,’ as a response that is reported or recorded in the wrong category; for example, a variable is registered as a one when it should have the value zero. Misclassification can easily happen in any data; for example, in an interview setting where the respondent misunderstands the question or the interviewer checks the wrong box. …


Jmasm 51: Bayesian Reliability Analysis Of Binomial Model – Application To Success/Failure Data, M. Tanwir Akhtar, Athar Ali Khan Mar 2019

Jmasm 51: Bayesian Reliability Analysis Of Binomial Model – Application To Success/Failure Data, M. Tanwir Akhtar, Athar Ali Khan

Journal of Modern Applied Statistical Methods

Reliability data are generated in the form of success/failure. An attempt was made to model such type of data using binomial distribution in the Bayesian paradigm. For fitting the Bayesian model both analytic and simulation techniques are used. Laplace approximation was implemented for approximating posterior densities of the model parameters. Parallel simulation tools were implemented with an extensive use of R and JAGS. R and JAGS code are developed and provided. Real data sets are used for the purpose of illustration.