Statistics and Probability Commons^™

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 …

Making Models With Bayes, Pilar Olid

Electronic Theses, Projects, and Dissertations

Bayesian statistics is an important approach to modern statistical analyses. It allows us to use our prior knowledge of the unknown parameters to construct a model for our data set. The foundation of Bayesian analysis is Bayes' Rule, which in its proportional form indicates that the posterior is proportional to the prior times the likelihood. We will demonstrate how we can apply Bayesian statistical techniques to fit a linear regression model and a hierarchical linear regression model to a data set. We will show how to apply different distributions to Bayesian analyses and how the use of a prior affects …

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 …

Probability Models And Compounding, David L. Farnsworth, James E. Marengo

Articles

We present the case that the ideas contained in a particular sequence of formulas are important in probability and statistics. The synthesis offered by the concepts in the sequence can be very valuable. Facility with this sequence and its underpinnings should be in the skill set of anyone who uses or studies probability or statistics. For illustrative purposes, we give applications to mixture distributions and Bayesian analyses.

Diagnostics For Choosing Between Stratified Logrank And Stratified Wilcoxon, Jhoanne Marsh C. Gatpatan

Dissertations

Martinez and Naranjo (2010) proposed a pretest for choosing between Logrank or Wilcoxon test in a two - sample case. However, in the presence of covariates, comparing two populations without adjusting for covariates would yield misleading results. In this study, we propose several pretests that will help the analyst decide to use stratified Logrank or stratified Wilcoxon tests in comparing two survival curves after covariates have been taken into account. Power performance of each adaptive test was done through simulations under PH and non-PH cases.

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 …

The Impact Of Economic Recession On The Health Of Adult Nevadans, Ariana Goertz

UNLV Theses, Dissertations, Professional Papers, and Capstones

Recessions are generally considered to cause negative consequences, but recent studies have provided evidence that some health outcomes improve as the economy deteriorates. The relationship between economic downfalls and health is not straightforward; it is important to look at how health has been impacted in one of the areas hit hardest by the recession. Las Vegas, Nevada was previously considered recession-proof, seemingly unaffected by previous economic downturns exhibited by the rest of the country. However, during the Great Recession of 2007-2009, Las Vegas led the country in highest rates of unemployment and foreclosures. This was quite a collapse for a …

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 …

Exact Approaches For Bias Detection And Avoidance With Small, Sparse, Or Correlated Categorical Data, Sarah E. Schwartz

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Every day, traditional statistical methodology are used world wide to study a variety of topics and provides insight regarding countless subjects. Each technique is based on a distinct set of assumptions to ensure valid results. Additionally, many statistical approaches rely on large sample behavior and may collapse or degenerate in the presence of small, spare, or correlated data. This dissertation details several advancements to detect these conditions, avoid their consequences, and analyze data in a different way to yield trustworthy results.

One of the most commonly used modeling techniques for outcomes with only two possible categorical values (eg. live/die, pass/fail, …

Application Of Machine Learning And Statistical Learning Methods For Prediction In A Large-Scale Vegetation Map, Carla M. Brookey

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Original analyses of a large vegetation cover dataset from Roosevelt National Forest in northern Colorado were carried out by Blackard (1998) and Blackard and Dean (1998; 2000). They compared the classification accuracies of linear and quadratic discriminant analysis (LDA and QDA) with artificial neural networks (ANN) and obtained an overall classification accuracy of 70.58% for a tuned ANN compared to 58.38% for LDA and 52.76% for QDA.

Because there has been tremendous development of machine learning classification methods over the last 35 years in both computer science and statistics, as well as substantial improvements in the speed of computer hardware, …

Analysis Of A M/M/C Queue With Single And Multiple Synchronous Working Vacations, Shakir Majid, P. Manoharan

Applications and Applied Mathematics: An International Journal (AAM)

We consider a M/M/c queuing system with synchronous working vacation and two different policies of working vacation i.e. a multiple working vacation policy and a single working policy. During a working vacation the server does not completely halts the service rather than it will render service at a lower rate. In synchronous vacation policy all the servers leave for a vacation simultaneously, when the server finds the system empty after finishing serving a customer. In multiple working vacation (MWV) policy the servers continue to take vacation till they find the system nonempty at a vacation completion instant. Single working vacation …

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 …