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Full-Text Articles in Applied Statistics

Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo May 2017

Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo

Journal of Modern Applied Statistical Methods

Trimmed elemental regression is robust to outliers and violations of model assumptions. Its properties and statistical inference were evaluated using bias-corrected and accelerated bootstrap confidence intervals. An R package named TEEReg is developed to compute the trimmed elemental estimates and the corresponding bootstrap confidence intervals. Two examples are provided to demonstrate its usage.


Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks May 2017

Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks

Journal of Modern Applied Statistical Methods

The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined and compared with the effectiveness of nonparametric methods and Winsorizing in minimizing the impact of outliers. Results showed that, considering both power and Type I error, a nonparametric test is the safest choice to control the inflation of Type I error with a decent sample size and yield relatively high power.


Book Review: Multivariate Statistical Methods, A Primer, C. R. Rao May 2017

Book Review: Multivariate Statistical Methods, A Primer, C. R. Rao

Journal of Modern Applied Statistical Methods

Multivariate Statistical Methods, A Primer, 4th Ed. Bryan F. J. Manly and Jorge A. Navarro Alberto. NY: Chapman & Hall / CRC Press. 2016. 264 p. ISBN 10: 1498728960 / ISBN 13: 978-1498728966


Jmasm44: Implementing Multiple Ratio Imputation By The Emb Algorithm (R), Masayoshi Takahashi May 2017

Jmasm44: Implementing Multiple Ratio Imputation By The Emb Algorithm (R), Masayoshi Takahashi

Journal of Modern Applied Statistical Methods

Although single ratio imputation is often used to deal with missing values in practice, there is a paucity of discussion regarding multiple ratio imputation. Code in the R statistical environment is presented to execute multiple ratio imputation by the Expectation-Maximization with Bootstrapping (EMB) algorithm.


Assessing The Relationship Between Change Blindness And The Anchoring Effect, Melissa Schoenlein May 2017

Assessing The Relationship Between Change Blindness And The Anchoring Effect, Melissa Schoenlein

Honors Projects

A lack of consideration for all aspects of a question prompts fragmented decision making. These decisions, as they leave out fundamental information, repeatedly then lead to a potentially problematic reaction to the target question or stimuli. The anchoring heuristic propels one to make a decision, usually an estimate, based on a presented “fact”, often ignoring additional background and environmental clues. Reducing the rate of occurrence of the anchoring bias is thought to lead to an increase in holistic decision making. To promote this reduction, the purpose of this research was to affirmexamine the relationship between the susceptibility to change blindness …


A Review Of The Multiple-Sample Tests For The Continuous-Data Type, Dewi Rahardja Jan 2017

A Review Of The Multiple-Sample Tests For The Continuous-Data Type, Dewi Rahardja

Journal of Modern Applied Statistical Methods

For continuous data, various statistical hypotheses testing methods have been extensively discussed in the literature. In this article a review is provided of the multiple-sample continuous-data testing methods. It includes traditional methods, such as the two-sample t-test, Welch ANOVA test, etc., as well as newly-developed ones, such as the various Multiple Comparison Procedure (MCP). A roadmap is provided in a figure or diagram format as to which methods are available in the literature. Additionally, the implementation of these methods in popular statistical software packages such as SAS is also presented. This review will be helpful to determine which continuous-data testing …


Factor Analysis By Limited Scales: Which Factors To Analyze?, Stan Lipovetsky Jan 2017

Factor Analysis By Limited Scales: Which Factors To Analyze?, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Factor Analysis (FA) and Principal Component Analysis (PCA) are well-known main tools of the multivariate statistics for data analysis, reduction, and visualization. Commonly, the analysis and interpretation of their solutions is performed for each of several main eigenvectors with variances explaining a big part of the total variability in data. The recommendation is to determine if all the main vectors are really needed in the analysis, or some of them should be skipped if they correspond to the absence of the analyzing features. A simple criterion for identifying redundant vectors of loadings is their negative correlation with the vector of …


Prediction Of Percent Change In Linear Regression By Correlated Variables, Stan Lipovetsky Jan 2017

Prediction Of Percent Change In Linear Regression By Correlated Variables, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Multiple linear regression can be applied for predicting an individual value of dependent variable y by the given values of independent variables x. But it is not immediately clear how to estimate percent change in y due to changes in predictors, especially when those are correlated. This work considers several approaches to this problem, including its formulation via predictors adjusted by their correlation structure. Ordinary least squares regression is used, together with Shapley value regression and another model based on solving some system of differential equations. Numerical estimations performed for a real marketing research data demonstrate meaningful results. The considered …


Meta-Analyses Of The Relationship Between Depression And Nine Dimensions Of Perfectionism, Gabriel Lynn Hottinger Jan 2017

Meta-Analyses Of The Relationship Between Depression And Nine Dimensions Of Perfectionism, Gabriel Lynn Hottinger

Electronic Theses and Dissertations

Perfectionism has been shown to be related to depression, but perfectionism is multidimensional. Some dimensions are related to positive psychological characteristics and outcomes and other dimensions are related to negative psychological characteristics and outcomes. This study reports results of nine meta-analyses performed to investigate the association between each of nine subscales of perfectionism and depression to determine which dimensions of perfectionism are most strongly associated with depression. The two subscales that were used from the Hewitt and Flett (1991b) Multidimensional Perfectionism scale were Self-Oriented Perfectionism (SOP) and Socially-Prescribed Perfectionism (SPP). The five subscales that were used from the Frost et …


Barriers To Counseling Among Human Service Professionals: The Development And Validation Of The Fit, Stigma, & Value Scale, Edward S. Neukrug, Michael T. Kalkbrenner, Sandy-Ann M. Griffith Jan 2017

Barriers To Counseling Among Human Service Professionals: The Development And Validation Of The Fit, Stigma, & Value Scale, Edward S. Neukrug, Michael T. Kalkbrenner, Sandy-Ann M. Griffith

Counseling & Human Services Faculty Publications

This study sought to confirm rates of attendance in counseling of human service professionals and validate a 32-item questionnaire designed to identify barriers to counseling seeking behavior among this population. Results indicated that a large percentage of human service professionals attend counseling, with males and females attending at similar rates and non-Caucasians attending at lower rates. A multivariate analysis of variance and descriptive statistics identified the most common barriers to attendance in counseling and examined demographic differences in participants’ sensitivity towards barriers to attendance in counseling. A Principal Factor Analysis (PFA) revealed three subscales (fit, value, and stigma), which we …


Statistics-Bierce Library Study, Tyler J. Hushour Jan 2017

Statistics-Bierce Library Study, Tyler J. Hushour

Williams Honors College, Honors Research Projects

This is a report from two surveys that I created and administered to students and faculty at Bierce library who came to the Circulation Desk or the Tech Desk, as well as some of my other findings when periodically looking around the library to see where students like to study or hang-out. There was a written survey given at the Circulation Desk, and a different survey given at the Tech Check-Out Desk. The project is for Melanie Smith-Farrell, the head of Access Services, and is based on a similar study Ian McCullough did in the science library. While this is …


Approximate Bayesian Computation In Forensic Science, Jessie H. Hendricks Jan 2017

Approximate Bayesian Computation In Forensic Science, Jessie H. Hendricks

The Journal of Undergraduate Research

Forensic evidence is often an important factor in criminal investigations. Analyzing evidence in an objective way involves the use of statistics. However, many evidence types (i.e., glass fragments, fingerprints, shoe impressions) are very complex. This makes the use of statistical methods, such as model selection in Bayesian inference, extremely difficult.

Approximate Bayesian Computation is an algorithmic method in Bayesian analysis that can be used for model selection. It is especially useful because it can be used to assign a Bayes Factor without the need to directly evaluate the exact likelihood function - a difficult task for complex data. Several criticisms …


An Empirical Demonstration Of The Need For Exact Tests, Vance W. Berger Jan 2017

An Empirical Demonstration Of The Need For Exact Tests, Vance W. Berger

Journal of Modern Applied Statistical Methods

The robustness of parametric analyses is rarely questioned or qualified. Robustness, generally understood, means the exact and approximate p-values will lie on the same side of alpha for any reasonable data set; and 1) any data set would qualify as reasonable and 2) robustness holds universally, for all alpha levels and approximations. For this to be true, the approximation would need to be perfect all of the time. Any discrepancy between the approximation and the exact p-value, for any combination of alpha level and data set, would constitute a violation. Clearly, this is not true, and when confronted with this …


Economic Opportunity And Young Adult Mortality: Variations By Race/Ethnicity And Gender, Jocelyn Mineo Dec 2016

Economic Opportunity And Young Adult Mortality: Variations By Race/Ethnicity And Gender, Jocelyn Mineo

Honors Projects

This study examines the relationship between economic opportunity and adolescent and young adult mortality in the United States. In addition, this study explores other variables, such as social support and rurality, and their link to young adult mortality rates. First, we examined the link between economic opportunity and all-cause mortality rates for youth ages 15 to 34 in the United States. Given the increasing racial and ethnic diversity of America’s youth, we pay particular attention to race/ethnic differences. We also examine the differences in mortality by gender.


Longitudinal Stability Of Effect Sizes In Education Research, Joshua Stephens Nov 2016

Longitudinal Stability Of Effect Sizes In Education Research, Joshua Stephens

Journal of Modern Applied Statistical Methods

Educators use meta-analyses to decide best practices. It has been suggested that effect sizes have declined over time due to various biases. This study applies an established methodological framework to educational meta-analyses and finds that effect sizes have increased from 1970–present. Potential causes for this phenomenon are discussed.


The Application Of Legendre Multiwavelet Functions In Image Compression, Elham Hashemizadeh, Sohrab Rahbar Nov 2016

The Application Of Legendre Multiwavelet Functions In Image Compression, Elham Hashemizadeh, Sohrab Rahbar

Journal of Modern Applied Statistical Methods

Legendre multiwavelets are introduced. These functions can be designed in such a way that the properties of orthogonality, polynomial approximation, and symmetry hold at the same time. In this way, they can be effectively deployed in image compression.


Fitting Flexible Parametric Regression Models With Gldreg In R, Steve Su Nov 2016

Fitting Flexible Parametric Regression Models With Gldreg In R, Steve Su

Journal of Modern Applied Statistical Methods

This article outlines the functionality of the GLDreg package in R which fits parametric regression models using generalized lambda distributions via maximum likelihood estimation and L moment matching. The main advantage of GLDreg is the provision of robust regression lines and smooth regression quantiles beyond the capabilities of existing known methods.


Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications, Tabassum Sindhu, Navid Feroze, Muhammad Aslam Nov 2016

Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications, Tabassum Sindhu, Navid Feroze, Muhammad Aslam

Journal of Modern Applied Statistical Methods

Finite mixture distributions consist of a weighted sum of standard distributions and are a useful tool for reliability analysis of a heterogeneous population. They provide the necessary flexibility to model failure distributions of components with multiple failure models. The analysis of the mixture models under Bayesian framework has received sizable attention in the recent years. However, the Bayesian estimation of the mixture models under doubly censored samples has not yet been introduced in the literature. The main objective of this paper is to discuss the Bayes estimation of the inverse Weibull mixture distributions under doubly censoring. Different priors and loss …


Bayesian Analysis Of Discrete Skewed Laplace Distribution, A. Hossianzadeh, K Zare Nov 2016

Bayesian Analysis Of Discrete Skewed Laplace Distribution, A. Hossianzadeh, K Zare

Journal of Modern Applied Statistical Methods

The discrete skewed Laplace distribution is a flexible distribution with integer domain and simple closed form that can be applied to model count data. Parameters are estimated under empirical Bayes (EB) analysis and comparison are made between the Bayesian parameter estimation and classical parameter estimation, i.e. the maximum likelihood (ML) approach. The results show that the Bayesian parameter estimations are preferable.


A Comparison Of Usual T-Test Statistic And Modified T-Test Statistics On Skewed Distribution Functions, Wooi K. Lim, Alice W. Lim Nov 2016

A Comparison Of Usual T-Test Statistic And Modified T-Test Statistics On Skewed Distribution Functions, Wooi K. Lim, Alice W. Lim

Journal of Modern Applied Statistical Methods

When the sample size n is small, the random variable T= √n(\overline{X} – μ)/S is said to follow a central t distribution with degrees of freedom (n – 1), where \overline{X} is the sample mean and S is the sample standard deviation, provided that the data X ~ N (μ, σ2). The random variable T can be used as a test statistic to hypothesize the population mean μ. Some argue that the t-test statistic is robust against the normality of the distribution and claim that the normality assumption is not necessary. In this …


Designing Of Bayesian Skip Lot Sampling Plan Under Destructive Testing, K. K. Suresh, S. Umamaheswari Nov 2016

Designing Of Bayesian Skip Lot Sampling Plan Under Destructive Testing, K. K. Suresh, S. Umamaheswari

Journal of Modern Applied Statistical Methods

Skip-lot sampling plan serves as a cost-effective technique to manage the cost of performing frequent product inspections. As a powerful tool within a real-time quality management system, the ability to collect data which an optimize skip-lot sampling parameters affords manufacturers the luxury of lowering inspection expenses in various manufacturing units. The good quality of product can be produced in continuous improvement of production process in excellent quality history for suppliers. The procedures and necessary tables are provided for finding the respective plans for which sum of producer and consumer risks are minimized with acceptable and limiting quality levels which accounts …


Bayesian Inference For Median Of The Lognormal Distribution, K. Aruna Rao, Juliet Gratia D'Cunha Nov 2016

Bayesian Inference For Median Of The Lognormal Distribution, K. Aruna Rao, Juliet Gratia D'Cunha

Journal of Modern Applied Statistical Methods

Lognormal distribution has many applications. The past research papers concentrated on the estimation of the mean of this distribution. This paper develops credible interval for the median of the lognormal distribution. The estimated coverage probability and average length of the credible interval is compared with the confidence interval using Monte Carlo simulation.


The Br2 – Weighting Method For Estimating The Effects Of Air Pollution On Population Health, Goran Krstic, Nikolas S. Krstic, Mauricio Zambrano-Bigiarini Nov 2016

The Br2 – Weighting Method For Estimating The Effects Of Air Pollution On Population Health, Goran Krstic, Nikolas S. Krstic, Mauricio Zambrano-Bigiarini

Journal of Modern Applied Statistical Methods

Uncertainties, limitations and biases may impede the correct application of concentration-response linear functions to estimate the effects of air pollution exposure on population health. The reliability of a prediction depends largely on the strength of the linear correlation between the studied variables. This work proposes the joint use of the coefficient of determination, r2, with the regression slope, b, as an improved measure of the strength of the linear relation between air pollution and its effects on population health. The proposed br2‑weighting method offers more reliable inferences about the potential effects of air pollution on …


Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data, Iman Makhdoom, Parviz Nasiri, Abbas Pak Nov 2016

Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data, Iman Makhdoom, Parviz Nasiri, Abbas Pak

Journal of Modern Applied Statistical Methods

The problem of estimating the parameter of Exponential distribution on the basis of type II censoring scheme is considered when the available data are in the form of fuzzy numbers. The Bayes estimate of the unknown parameter is obtained by using the approximation forms of Lindley (1980) and Tierney and Kadane (1986) under the assumption of gamma prior. The highest posterior density (HPD) estimate of the parameter of interest is found. A Monte Carlo simulation is used to compare the performances of the different methods. A real data set is investigated to illustrate the applicability of …


Preliminary Tests Of Normality When Comparing Three Independent Samples, Björn Lantz, Roy Andersson, Peter Manfredsson Nov 2016

Preliminary Tests Of Normality When Comparing Three Independent Samples, Björn Lantz, Roy Andersson, Peter Manfredsson

Journal of Modern Applied Statistical Methods

This paper uses simulation to explore the performance of a two-stage procedure where a preliminary Shapiro-Wilk test is used to choose between the ANOVA and Kruskal-Wallis tests as a three-sample location test. The results suggest that the two-stage procedure actually seems to be preferable when conducting such location tests.


Limited Failure Censored Life Test Sampling Plan In Burr Type X Distribution, R. R. L. Kantam, M. S. Ravikumar Nov 2016

Limited Failure Censored Life Test Sampling Plan In Burr Type X Distribution, R. R. L. Kantam, M. S. Ravikumar

Journal of Modern Applied Statistical Methods

The Burr type X distribution is considered as a life time random variable of a product whose lots are to be decided for acceptance or otherwise on the basis of sample lifetimes drawn from the lot. The sample is divided into various groups in order to develop a group sampling plan in such a way that the life testing experiment is terminated as soon as the first failure in each group is observed. The acceptance criterion based on the theory of order statistics is proposed and is shown to be more economical than a criterion proposed in the earlier similar …


Comparison Of Some Multivariate Nonparametric Tests In Profile Analysis To Repeated Measurements, Mehrdad Vossoughi, Shila Shahvali, Erfan Sadeghi Nov 2016

Comparison Of Some Multivariate Nonparametric Tests In Profile Analysis To Repeated Measurements, Mehrdad Vossoughi, Shila Shahvali, Erfan Sadeghi

Journal of Modern Applied Statistical Methods

Through Monte Carlo simulations, the performance of six multivariate nonparametric tests for testing the hypothesis of parallelism in profile analysis was studied. In conclusion, the tests based on ranks were as efficient as Hotelling's T2 under multivariate normal distribution. For the heavy tailed distribution, the tests based on signs performed best.


On Generalizing Cumulative Ordered Regression Models, Robert W. Walker Nov 2016

On Generalizing Cumulative Ordered Regression Models, Robert W. Walker

Journal of Modern Applied Statistical Methods

We examine models that relax proportionality in cumulative ordered regression models. Something fundamental arising from ordered variables and stochastic ordering implies a partitioning. Efforts to relax proportionality also relax the ability to collapse an inherently multidimensional problem to a partitioning of the (unidimensional) real line. It is surprising and unfortunate to find that deviations from proportionality are sufficient to generate internal contradictions; undecidable propositions must exist by relaxing proportional odds without other relevant and significant changes in the underlying model. We prove a single theorem linking continuous support and partitions of a latent space to show that for these two …


End Matter, Jmasm Editors Nov 2016

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Some Remarks On Rao And Lovric’S ‘Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective’, Bruno D. Zumbo, Edward Kroc Nov 2016

Some Remarks On Rao And Lovric’S ‘Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective’, Bruno D. Zumbo, Edward Kroc

Journal of Modern Applied Statistical Methods

Although we have much to agree with in Rao and Lovric’s important discussion of the test of point null hypotheses, it stirred us to provide a way out of their apparent Zero probability paradox and cast the Hodges-Lehmann paradigm from a Serlin-Lapsley approach. We close our remarks with an eye toward a broad perspective.