Statistics and Probability Commons^™

'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 …

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari

Journal of Modern Applied Statistical Methods

The characterizations of a certain class of probability distributions are established through conditional expectation of lower record values when the conditioned record value may not be the adjacent one. Some of its important deductions are also discussed.

Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

When running a confirmatory factor analysis (CFA), users specify and interpret the pattern (loading) matrix. It has been recommended that the structure coefficients, indicating the factors’ correlation with the observed indicators, should also be reported when the factors are correlated (Graham, Guthrie, & Thompson, 2003; Thompson, 1997). The aims of this article are: (1) to note the structure coefficient should be interpreted with caution if the factors are specified to correlate. Because the structure coefficient is a zero-order correlation, it may be partially or entirely a reflection of factor correlations. This is elucidated by the matrix algebra of the structure …

A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer

Journal of Modern Applied Statistical Methods

Industrial process use single and double Exponential Weighted Moving Average control charts to detect small shifts in it. Occasionally there is a need to detect small trends instead of shifts, but the effectiveness to detect small trends. A new control chart is proposed to detect a small drift.

Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques

Journal of Modern Applied Statistical Methods

The relationships resulting from the dichotomization of multivariate normal data is a question that causes concern when using exploratory factor analysis. The relationships in an exploratory factor analysis are examined when multivariate normal data, generated by Monte Carlo methods, is dichotomized.

Power And Sample Size Estimation For Nonparametric Composite Endpoints: Practical Implementation Using Data Simulations, Paul M. Brown, Justin A. Ezekowitz

Journal of Modern Applied Statistical Methods

Composite endpoints are a popular outcome in controlled studies. However, the required sample size is not easily obtained due to the assortment of outcomes, correlations between them and the way in which the composite is constructed. Data simulations are required. A macro is developed that enables sample size and power estimation.

Does The Stress Inherent To Laboratory Life And Experimentation On Animals Adversely Affect Research Data?, Jarrod Bailey

Validation of Animal Experimentation Collection

Stress and distress in laboratory animals is often inherent and unavoidable. The effect of these factors on the reliability and relevance of experimental data is not sufficiently appreciated. Greater awareness, debate and discussion of this issue are urgently required.

Hemodynamic Characteristics Of Ruptured And Unruptured Multiple Aneurysms At Mirror And Ipsilateral Locations, Ravi Doddasomayajula, Bong Jae Chung, Fernando Mut, Carlos M. Jimenez, Farid Hamzei-Sichani, Christopher M. Putman, Juan R. Cebral

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

BACKGROUND AND PURPOSE: Different hemodynamic patterns have been associated with aneurysm rupture. The objective was to test whether hemodynamic characteristics of the ruptured aneurysm in patients with multiple aneurysms were different from those in unruptured aneurysms in the same patient.

MATERIALS AND METHODS: Twenty-four mirror and 58 ipsilateral multiple aneurysms with 1 ruptured and the others unruptured were studied. Computational fluid dynamics models were created from 3D angiographies. Case-control studies of mirror and ipsilateral aneurysms were performed with paired Wilcoxon tests.

RESULTS: In mirror pairs, the ruptured aneurysm had more oscillatory wall shear stress (P = .007) than the …

Novel Statistical Models For Quantitative Shape-Gene Association Selection, Xiaotian Dai

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Other research reported that genetic mechanism plays a major role in the development process of biological shapes. The primary goal of this dissertation is to develop novel statistical models to investigate the quantitative relationships between biological shapes and genetic variants. However, these problems can be extremely challenging to traditional statistical models for a number of reasons: 1) the biological phenotypes cannot be effectively represented by single-valued traits, while traditional regression only handles one dependent variable; 2) in real-life genetic data, the number of candidate genes to be investigated is extremely large, and the signal-to-noise ratio of candidate genes is expected …

The Regression Smoother Lowess: A Confidence Band That Allows Heteroscedasticity And Has Some Specified Simultaneous Probability Coverage, Rand Wilcox

Journal of Modern Applied Statistical Methods

Many nonparametric regression estimators (smoothers) have been proposed that provide a more flexible method for estimating the true regression line compared to using some of the more obvious parametric models. A basic goal when using any smoother is computing a confidence band for the true regression line. Let M(Y|X) be some conditional measure of location associated with the random variable Y, given X and let x be some specific value of the covariate. When using the LOWESS estimator, an extant method that assumes homoscedasticity can be used to compute a confidence interval for M(Y|X = x). A trivial way of …

Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix

Journal of Modern Applied Statistical Methods

Variable importance measures based on discriminant analysis and multivariate analysis of variance are useful for identifying variables that discriminate between two groups in multivariate group designs. Variable importance measures are developed based on trimmed and Winsorized estimators for describing group differences in multivariate non-normal populations.

Effectively Comparing Differences In Proportions, Lonnie Turpin Jr.

Journal of Modern Applied Statistical Methods

A single framework of developing and implementing tests about proportions is outlined. It avoids some of the pitfalls of methods commonly put forward in an introductory data analysis course.

Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker

Journal of Modern Applied Statistical Methods

Using a simulation study, the performance of complete case analysis, full information maximum likelihood, multivariate normal imputation, multiple imputation by chained equations and two-fold fully conditional specification to handle missing data were compared in longitudinal surveys with continuous and binary outcomes, missing covariates, and an interaction term.

Around Gamma Lindley Distribution, Hamouda Messaadia, Halim Zeghdoudi

Journal of Modern Applied Statistical Methods

Some remarks and correction on a new distribution, Gamma Lindley, of which the Lindley distribution is a particular case, are given pertaining to its parameter space.

The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel

Journal of Modern Applied Statistical Methods

Previous studies that explored the impact of misspecification of cross-classified data structure as strictly hierarchical are limited to random intercept models. This study examined the effects of misspecification of a two-level, cross-classified, random effect model (CCREM) where both the level-1 intercept and slope were allowed to vary randomly. Results suggest that ignoring one of the crossed factors produced considerably underestimated standard errors for: 1) the regression coefficients of the level-1 predictor; 2) the inappropriately modeled predictor associated with the misspecified crossed factor; and 3) and their interaction. This misspecification also resulted in a significant inflation of the level-1 residual variances …

Experimental Design And Data Analysis In Computer Simulation Studies In The Behavioral Sciences, Michael Harwell, Nidhi Kohli, Yadira Peralta

Journal of Modern Applied Statistical Methods

Treating computer simulation studies as statistical sampling experiments subject to established principles of experimental design and data analysis should further enhance their ability to inform statistical practice and a program of statistical research. Latin hypercube designs to enhance generalizability and meta-analytic methods to analyze simulation results are presented.

On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja

Journal of Modern Applied Statistical Methods

Balanced incomplete block designs are not always possible to construct because of their parametric relations. In such a situation another balanced design, the variance balanced design, is required. This construction of binary, equal replicated variance balanced designs are discussed using the half fraction of the 2n factorial designs with smaller block sizes. This method was also extended to construct another variance balanced design by deleting the last block of the resulting variance balanced designs. Its efficiency factor compared with randomized block designs was compared and found to be highly efficient.

Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson

Journal of Modern Applied Statistical Methods

The aim of this study was to investigate the performance of the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) confidence intervals methods for the non-parametric reliability estimate, ordinal alpha. All methods yielded unacceptably low coverage rates and potentially increased Type-I error rates.

A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum

Journal of Modern Applied Statistical Methods

Monte Carlo simulations are used to investigate the effect of two factors, the amount of variability and an outlier, on the size of the Pearson correlation coefficient. Some simulation algorithms are developed, and two theorems for increasing or decreasing the amount of variability are suggested.

Parameter Estimation In Weighted Rayleigh Distribution, M. Ajami, S. M. A. Jahanshahi

Journal of Modern Applied Statistical Methods

A weighted model based on the Rayleigh distribution is proposed and the statistical and reliability properties of this model are presented. Some non-Bayesian and Bayesian methods are used to estimate the β parameter of proposed model. The Bayes estimators are obtained under the symmetric (squared error) and the asymmetric (linear exponential) loss functions using non-informative and reciprocal gamma priors. The performance of the estimators is assessed on the basis of their biases and relative risks under the two above-mentioned loss functions. A simulation study is constructed to evaluate the ability of considered estimation methods. The suitability of the proposed model …

Jmasm 46: Algorithm For Comparison Of Robust Regression Methods In Multiple Linear Regression By Weighting Least Square Regression (Sas), Mohamad Shafiq, Wan Muhamad Amir, Nur Syabiha Zafakali

Journal of Modern Applied Statistical Methods

The aim of this study is to compare different robust regression methods in three main models of multiple linear regression and weighting multiple linear regression. An algorithm for weighting multiple linear regression by standard deviation and variance for combining different robust method is given in SAS along with an application.

Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya

Journal of Modern Applied Statistical Methods

The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the …

Survival Analysis: A Modified Kaplan-Meir Estimator, Justin A. Bancroft

Graduate Theses/Dissertations

The popular Kaplan-Meir estimator has traditionally been used to great effect as a survival function estimator. However, the Kaplan-Meir estimator is dependent upon a maximum likelihood parameter estimator which may not be the best estimator in all cases. We modify the Kaplan-Meir estimator, based on a Bayes parameter estimation, in hopes of providing a more accurate survival estimator for small sample sizes. Core elements of survival analysis are presented, acting as a foundation from which to construct and compare our modified Kaplan-Meir estimator. It is hypothesized that our modified Kaplan-Meir estimator is generally more accurate than the standard Kaplan-Meir estimator …

Reliability Of An Observational Method Used To Assess Tennis Serve Mechanics In A Group Of Novice Raters, Natalie L. Myers, W. Ben Kibler, Gilson J. Capilouto, Philip M. Westgate, Tony English, Timothy L. Uhl

Physical Therapy Faculty Publications

Background: Previous research has developed an observational tennis serve analysis (OTSA) tool to assess serve mechanics. The OTSA has displayed substantial agreement between the two health care professionals that developed the tool; however, it is currently unknown if the OTSA is reliable when administered by novice users.

Purpose: The purpose of this investigation was to determine if reliability for the OTSA could be established in novice users via an interactive classroom training session.

Methods: Eight observers underwent a classroom instructional training protocol highlighting the OTSA. Following training, observers participated in two different rating sessions approximately a week apart. Each observer …

A Customized Quantitative Pcr Microrna Panel Provides A Technically Robust Context For Studying Neurodegenerative Disease Biomarkers And Indicates A High Correlation Between Cerebrospinal Fluid And Choroid Plexus Microrna Expression, Wang-Xia Wang, David W. Fardo, Gregory A. Jicha, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNA (miRNA) expression varies in association with different tissue types and in diseases. Having been found in body fluids including blood and cerebrospinal fluid (CSF), miRNAs constitute potential biomarkers. CSF miRNAs have been proposed as biomarkers for neurodegenerative diseases; however, there is a lack of consensus about the best candidate miRNA biomarkers and there has been variability in results from different research centers, perhaps due to technical factors. Here, we sought to optimize technical parameters for CSF miRNA studies. We examined different RNA isolation methods and performed miRNA expression profiling with TaqMan® miRNA Arrays. More specifically, we developed a customized …

Reassessment Of The Red Drum Stock In Mississippi Coastal Waters: The Role Of Ages 3-5 Year-Class Fish, Emily Satterfield

Master's Theses

Red Drum, Sciaenops ocellatus, are highly sought after by sport fishermen in Mississippi coastal waters. In 2016, Mississippi anglers made over 180,000 fishing trips targeting Red Drum, making it the second most targeted marine species. The current Fishery Management Plan of the Gulf of Mexico Fishery Management Council, prohibits harvest of Red Drum in federal waters. Monitoring of the stock in Mississippi state waters occurs at sites that are almost exclusively estuarine, using gear types selective for juvenile fish. Additional samples come from the for-hire-industry that typically targets larger Red Drum. This project’s goal was to target age three …

Functional Data Analysis Methods For Predicting Disease Status., Sarah Kendrick

Electronic Theses and Dissertations

Introduction: Differential scanning calorimetry (DSC) is used to determine thermally-induced conformational changes of biomolecules within a blood plasma sample. Recent research has indicated that DSC curves (or thermograms) may have different characteristics based on disease status and, thus, may be useful as a monitoring and diagnostic tool for some diseases. Since thermograms are curves measured over a range of temperature values, they are often considered as functional data. In this dissertation we propose and apply functional data analysis (FDA) techniques to analyze DSC data from the Lupus Family Registry and Repository (LFRR). The aim is to develop FDA methods to …

Transient Solution Of M[X1],M[X2]/G1,G2/1 With Priority Services, Modified Bernoulli Vacation, Bernoulli Feedback, Breakdown, Delaying Repair And Reneging, G. Ayyappan, J. Udayageetha

Applications and Applied Mathematics: An International Journal (AAM)

This paper considers a queuing system which facilitates a single server that serves two classes of units: high priority and low priority units. These two classes of units arrive at the system in two independent compound Poisson processes. It aims to decipher average queue size and average waiting time of the units. Under the pre-emptive priority rule, the server provides a general service to these arriving units. It is further assumed the server may take a vacation after serving the last high priority unit present in the system or at the service completion of each low priority unit present in …