Personal Foul: How Head Trauma And The Insurance Industry Are Threatening Sports,
2020
Liberty University
Personal Foul: How Head Trauma And The Insurance Industry Are Threatening Sports, Zachary Cooler
Senior Honors Theses
This thesis will investigate the growing problem of head trauma in contact sports like football, hockey, and soccer through medical studies, implications to the insurance industry, and ongoing litigation. The thesis will investigate medical studies that are finding more evidence to support the claim that contact sports players are more likely to receive head trauma symptoms such as memory loss, mood swings, and even Lou Gehrig’s disease in extreme cases. The thesis will also demonstrate that these medical symptoms and monetary losses from medical claims are convincing insurance companies to withdraw insurance coverage for sports leagues, which they are justifying …
Investigating The Performance Of Propensity Score Approaches For Differential Item Functioning Analysis,
2020
University of British Columbia
Investigating The Performance Of Propensity Score Approaches For Differential Item Functioning Analysis, Yan Liu, Chanmin Kim, Amrey D. Wu, Paul Gustafson, Edward Kroc, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
To evaluate the performance of propensity score approaches for differential item functioning analysis, this simulation study was conducted to assess bias, mean square error, Type I error, and power under different levels of effect size and a variety of model misspecification conditions, including different types and missing patterns of covariates.
Quasi-Likelihood Ratio Tests For Homoscedasticity In Linear Regression,
2020
Georgia Southern University
Quasi-Likelihood Ratio Tests For Homoscedasticity In Linear Regression, Lili Yu, Varadan Sevilimedu, Robert Vogel, Hani Samawi
Journal of Modern Applied Statistical Methods
Two quasi-likelihood ratio tests are proposed for the homoscedasticity assumption in the linear regression models. They require few assumptions than the existing tests. The properties of the tests are investigated through simulation studies. An example is provided to illustrate the usefulness of the new proposed tests.
A Glossary On Building Longitudinal, Population-Based Data Linkages To Explore Children’S Developmental Trajectories,
2020
University of British Columbia
A Glossary On Building Longitudinal, Population-Based Data Linkages To Explore Children’S Developmental Trajectories, Jennifer E. V. Lloyd, Jacqui Boonstra, Lisa Chen, Barry Forer, Ruth Hershler, Constance Milbrath, Brenda T. Poon, Neda Razaz, Pippa Rowcliffe, Kimberly Schonert-Reichl
Journal of Modern Applied Statistical Methods
Population-based, person-specific, longitudinal child and youth health and developmental data linkages involve connecting combinations of specially-collected data and administrative data for longitudinal population research purposes. This glossary provides definitions of key terms and concepts related to their theoretical basis, research infrastructure, research methodology, statistical analysis, and knowledge translation.
Robust Confidence Intervals For The Population Mean Alternatives To The Student-T Confidence Interval,
2020
The Hashemite University, Zarqa, Jordan
Robust Confidence Intervals For The Population Mean Alternatives To The Student-T Confidence Interval, Moustafa Omar Ahmed Abu-Shawiesh, Aamir Saghir
Journal of Modern Applied Statistical Methods
In this paper, three robust confidence intervals are proposed as alternatives to the Student‑t confidence interval. The performance of these intervals was compared through a simulation study shows that Qn-t confidence interval performs the best and it is as good as Student’s‑t confidence interval. Real-life data was used for illustration and performing a comparison that support the findings obtained from the simulation study.
Using Spss To Analyze Complex Survey Data: A Primer,
2020
University of British Columbia
Using Spss To Analyze Complex Survey Data: A Primer, Danjie Zou, Jennifer E. V. Lloyd, Jennifer L. Baumbusch
Journal of Modern Applied Statistical Methods
An introduction to using SPSS to analyze complex survey data is given. Key features of complex survey design are described briefly, including stratification, clustering, multiple stages, and weights. Then, annotated SPSS syntax for complex survey data analysis is presented to demonstrate the step-by-step process using real complex samples data.
On The Authentic Notion, Relevance, And Solution Of The Jeffreys-Lindley Paradox In The Zettabyte Era,
2020
Radford University
On The Authentic Notion, Relevance, And Solution Of The Jeffreys-Lindley Paradox In The Zettabyte Era, Miodrag M. Lovric
Journal of Modern Applied Statistical Methods
The Jeffreys-Lindley paradox is the most quoted divergence between the frequentist and Bayesian approaches to statistical inference. It is embedded in the very foundations of statistics and divides frequentist and Bayesian inference in an irreconcilable way. This paradox is the Gordian Knot of statistical inference and Data Science in the Zettabyte Era. If statistical science is ready for revolution confronted by the challenges of massive data sets analysis, the first step is to finally solve this anomaly. For more than sixty years, the Jeffreys-Lindley paradox has been under active discussion and debate. Many solutions have been proposed, none entirely satisfactory. …
Conflicts In Bayesian Statistics Between Inference Based On Credible Intervals And Bayes Factors,
2020
Radford University
Conflicts In Bayesian Statistics Between Inference Based On Credible Intervals And Bayes Factors, Miodrag M. Lovric
Journal of Modern Applied Statistical Methods
In frequentist statistics, point-null hypothesis testing based on significance tests and confidence intervals are harmonious procedures and lead to the same conclusion. This is not the case in the domain of the Bayesian framework. An inference made about the point-null hypothesis using Bayes factor may lead to an opposite conclusion if it is based on the Bayesian credible interval. Bayesian suggestions to test point-nulls using credible intervals are misleading and should be dismissed. A null hypothesized value may be outside a credible interval but supported by Bayes factor (a Type I conflict), or contrariwise, the null value may be inside …
A Monte Carlo Analysis Of Standard Error-Based Methods For Computing Confidence Intervals,
2020
Western Kentucky University
A Monte Carlo Analysis Of Standard Error-Based Methods For Computing Confidence Intervals, Elayna Wichert
Masters Theses & Specialist Projects
The objective of this study is to empirically test existing techniques to calculate the likely range of values for a Classical Test Theory true score given an observed score. The traditional method for forming these confidence intervals has used the standard error of measurement (SEM) as the basis for this confidence interval. An alternate equation, the standard error of estimate (SEE), has been recommended in place of the SEM for this purpose, yet it remains overlooked in the field of psychometrics. It is important that the correct equation be used in various applications in personnel psychology. Monte Carlo analyses were …
Sampling The Porridge: A Comparison Of Ordered Variable Regression With F And R2 And Multiple Linear Regression With Corrected F And R2 In The Presence Of Multicollinearity,
2020
Brown University
Sampling The Porridge: A Comparison Of Ordered Variable Regression With F And R2 And Multiple Linear Regression With Corrected F And R2 In The Presence Of Multicollinearity, Grayson L. Baird, Stephen L. Bieber
Journal of Modern Applied Statistical Methods
Differences between the multiple linear regression model with Corrected R2 and Corrected F and the ordered variable regression model with R2 and F when intercorrelation is present are illustrated with simulated and real-world data.
A New Liu Type Of Estimator For The Restricted Sur Estimator,
2020
Jönköping University
A New Liu Type Of Estimator For The Restricted Sur Estimator, Kristofer Månsson, B. M. Golam Kibria, Ghazi Shukur
Journal of Modern Applied Statistical Methods
A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity.
Parametric And Non-Parametric Tests For The Comparison Of Two Samples Which Both Include Paired And Unpaired Observations,
2020
University of the West of England
Parametric And Non-Parametric Tests For The Comparison Of Two Samples Which Both Include Paired And Unpaired Observations, Ben Derrick, Paul White, Deirdre Toher
Journal of Modern Applied Statistical Methods
Samples that include both independent and paired observations cause a dilemma for researchers that covers the full breadth of empirical research. Parametric approaches for the comparison of two samples using all available observations are considered, under normality and non-normality. These approaches are compared to naive and newly proposed non-parametric alternatives.
A Study Verifying The Dimensioning Of A Multivariate Dichotomized Sample In Exploratory Factor Analysis,
2020
Federal University of Paraná (UFPR)
A Study Verifying The Dimensioning Of A Multivariate Dichotomized Sample In Exploratory Factor Analysis, Rosilei S. Novak, Jair M. Marques
Journal of Modern Applied Statistical Methods
The sample size dichotomized was related to the measure of sampling adequacy, considering the explanations provided by factors and commonalities. Monte Carlo simulation generated multivariate normal samples and varying the number of observations, the factor analysis was applied in each sample dichotomized. Results were modeled by polynomial regression based on the sample sizing.
Inferences For Weibull-Gamma Distribution In Presence Of Partially Accelerated Life Test,
2020
Al-Azhar University - Egypt
Inferences For Weibull-Gamma Distribution In Presence Of Partially Accelerated Life Test, Mahmoud Mansour, M A W Mahmoud Prof., Rashad El-Sagheer
Basic Science Engineering
In this paper, the point at issue is to deliberate point and interval estimations for the parameters of Weibull-Gamma distribution (WGD) using progressively Type-II censored (PROG-II-C) sample under step stress partially accelerated life test (SSPALT) model. The maximum likelihood (ML), Bayes, and four parametric bootstrap methods are used to obtain the point estimations for the distribution parameters and the acceleration factor. Furthermore, the approximate confidence intervals (ACIs), four bootstrap confidence intervals and credible intervals of the estimators have been gotten. The results of Bayes estimators are computed under the squared error loss (SEL) function using Markov Chain Monte Carlo (MCMC) …
Small Area Estimation On Zero-Inflated Data Using Frequentist And Bayesian Approach,
2020
Bogor Agricultural University
Small Area Estimation On Zero-Inflated Data Using Frequentist And Bayesian Approach, Kusman Sadik, Rahma Anisa, Euis Aqmaliyah
Journal of Modern Applied Statistical Methods
The most commonly used method of small area estimation (SAE) is the empirical best linear unbiased prediction method based on a linear mixed model. However, it is not appropriate in the case of the zero-inflated target variable with a mixture of zeros and continuously distributed positive values. Therefore, various model-based SAE methods for zero-inflated data are developed, such as the Frequentist approach and the Bayesian approach. Both approaches are compared with the survey regression (SR) method which ignores the presence of zero-inflation in the data. The results show that the two SAE approaches for zero-inflated data are capable to yield …
Dynamic Conditional Correlation Garch: A Multivariate Time Series Novel Using A Bayesian Approach,
2020
University of Sao Paulo
Dynamic Conditional Correlation Garch: A Multivariate Time Series Novel Using A Bayesian Approach, Diego Nascimento, Cleber Xavier, Israel Felipe, Francisco Louzada Neto
Journal of Modern Applied Statistical Methods
The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation.
The Importance Of Type I Error Rates When Studying Bias In Monte Carlo Studies In Statistics,
2020
University of Minnesota - Twin Cities
The Importance Of Type I Error Rates When Studying Bias In Monte Carlo Studies In Statistics, Michael Harwell
Journal of Modern Applied Statistical Methods
Two common outcomes of Monte Carlo studies in statistics are bias and Type I error rate. Several versions of bias statistics exist but all employ arbitrary cutoffs for deciding when bias is ignorable or non-ignorable. This article argues Type I error rates should be used when assessing bias.
Bivariate Analogs Of The Wilcoxon–Mann–Whitney Test And The Patel–Hoel Method For Interactions,
2020
University of Southern California
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.
Regression When There Are Two Covariates: Some Practical Reasons For Considering Quantile Grids,
2020
University of Southern California
Regression When There Are Two Covariates: Some Practical Reasons For Considering Quantile Grids, Rand Wilcox
Journal of Modern Applied Statistical Methods
When dealing with the association between some random variable and two covariates, extensive experience with smoothers indicates that often a linear model poorly reflects the nature of the association. A simple approach via quantile grids that reflects the nature of the association is given. The two main goals are to illustrate this approach can make a practical difference, and to describe R functions for applying it. Included are comments on dealing with more than two covariates.
Assessing The Accuracy Of Approximate Confidence Intervals Proposed For The Mean Of Poisson Distribution,
2020
Velayat University of Iranshahr, Iran
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.
