Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies,
2017
University of Kentucky
Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin
Biostatistics Faculty Publications
Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values …
Flow Anisotropy Due To Thread-Like Nanoparticle Agglomerations In Dilute Ferrofluids,
2017
Montclair State University
Flow Anisotropy Due To Thread-Like Nanoparticle Agglomerations In Dilute Ferrofluids, Alexander Cali, Wah-Keat Lee, A. David Trubatch, Philip Yecko
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
Improved knowledge of the magnetic field dependent flow properties of nanoparticle-based magnetic fluids is critical to the design of biomedical applications, including drug delivery and cell sorting. To probe the rheology of ferrofluid on a sub-millimeter scale, we examine the paths of 550 μm diameter glass spheres falling due to gravity in dilute ferrofluid, imposing a uniform magnetic field at an angle with respect to the vertical. Visualization of the spheres’ trajectories is achieved using high resolution X-ray phase-contrast imaging, allowing measurement of a terminal velocity while simultaneously revealing the formation of an array of long thread-like accumulations of magnetic …
Analytics And Baseball's New Generation,
2017
University of North Dakota
Analytics And Baseball's New Generation, John Roche
Essential Studies UNDergraduate Showcase
Major League Baseball has been a catalyst for making decisions in sports and competition from a purely mathematical viewpoint. We have seen teams utilize unique on-field player alignments and roster-building strategies based on statistical observations and applications of math. This project examines the advantages Sabermetrics and analytics present within the sport. Untapped statistical categories that could further the success of teams in the future is also briefly discussed.
The Most Important Statistics In Football,
2017
University of North Dakota
The Most Important Statistics In Football, Jacob Holmen
Essential Studies UNDergraduate Showcase
This research is based on the Five Factors that were devised by Bill Connelly of SBNation. The Five Factors of football include Explosiveness, Efficiency, Field Position, Finishing Drives, and Turnovers. Each factor is composed of associated statistics that when put together make up the most important statistics in football. This research includes the analysis of all 857 FBS (the highest level of NCAA Division I football) games from the 2016 season. Data was analyzed through the use of an Excel spreadsheet. Five different statistics were looked at, each associated with one of the Five Factors. The statistics include Yards per …
How Is Your Productivity Affected Based On Your App Usage?,
2017
Chapman University
How Is Your Productivity Affected Based On Your App Usage?, Colette Noghreian
Student Scholar Symposium Abstracts and Posters
As technology becomes more prominent in society, it is crucial to investigate its effect on day to day life. The purpose of this study is to determine how the amount of time spent on iPhone applications affects how productive students feel in the span of one week. Results are tested through a survey which first determines general information about the student, and then guides students to navigate their phone settings and record the battery usage of the top three applications which use up the most battery. It is hypothesized that productivity decreases as battery usage increases due to the substantial …
Statistical Analysis Of Momentum In Basketball,
2017
Bowling Green State University
Statistical Analysis Of Momentum In Basketball, Mackenzi Stump
Honors Projects
The “hot hand” in sports has been debated for as long as sports have been around. The debate involves whether streaks and slumps in sports are true phenomena or just simply perceptions in the mind of the human viewer. This statistical analysis of momentum in basketball analyzes the distribution of time between scoring events for the BGSU Women’s Basketball team from 2011-2017. We discuss how the distribution of time between scoring events changes with normal game factors such as location of the game, game outcome, and several other factors. If scoring events during a game were always randomly distributed, or …
Fetal Growth Restriction: Case Definition & Guidelines For Data Collection, Analysis, And Presentation Of Immunization Safety Data,
2017
University of South Carolina
Fetal Growth Restriction: Case Definition & Guidelines For Data Collection, Analysis, And Presentation Of Immunization Safety Data, Sarah Rae Easter, Linda O. Eckert, Nansi Boghossian, Rebecca Spencer, Eugene Oteng-Ntim, Christos Ioannou, Manasi Patwardhan, Margo S. Harrison, Asma Khalil, Michael Gravett, Robert Goldenberg, Alastair Mckelvey, Manish Gupta, Vitali Pool, Stephen C. Robson, Jyoti Joshi, Sonali Kochhar, Tom Mcelrath
Faculty Publications
No abstract provided.
Small For Gestational Age: Case Definition & Guidelines For Data Collection, Analysis, And Presentation Of Maternal Immunisation Safety Data,
2017
University of South Carolina
Small For Gestational Age: Case Definition & Guidelines For Data Collection, Analysis, And Presentation Of Maternal Immunisation Safety Data, Elizabeth P. Schlaudecker, Flor M. Munoz, Azucena Bardají, Nansi S. Boghossian, Asma Khalil, Hatem Mousa, Mirjana Nesin, Muhammad Imran Nisar, Vitali Pool, Hans M.L. Spiegel, Milagritos D. Tapia, Sonali Kochhar, Steven Black
Faculty Publications
No abstract provided.
Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation,
2017
Abadan Branch, Islamic Azad University, Abadan, Iran
Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation, Ghasem Rekabdar, Rahim Chinipardaz
Journal of Modern Applied Statistical Methods
The quadratic form of non-central normal variables is presented based on a sum of weighted independent non-central chi-square variables. This presentation provides moments of quadratic form. The maximum entropy method is used to estimate the density function because distribution moments of quadratic forms are known. A Euclidean distance is proposed to select an appropriate maximum entropy density function. In order to compare with other methods some numerical examples were evaluated. Also, for discrimination between two groups by the Euclidean distances, we obtained a stochastic representation for the linear discriminant function using the quadratic form. The maximum entropy estimation was an …
Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model,
2017
Yarmouk University, Irbid, Jordan
Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous
Journal of Modern Applied Statistical Methods
Most reliability studies obtained reliability information by using degradation measurements over time, which contains useful data about the product reliability. Parametric methods like the maximum likelihood (ML) estimator and the ordinary least square (OLS) estimator are used widely to estimate the time-to-failure distribution and its percentiles. In this article, we estimate the time-to-failure distribution and its percentiles by using a semi-parametric estimator that assumes the parametric function to have a half- normal distribution or an exponential distribution. The performance of the semi-parametric estimator is compared via simulation study with the ML and OLS estimators by using the mean square error …
Jmasm 48: The Pearson Product-Moment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The Olkin-Pratt Adjustment (Spss),
2017
Northern Illinois University
Jmasm 48: The Pearson Product-Moment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The Olkin-Pratt Adjustment (Spss), David A. Walker
Journal of Modern Applied Statistical Methods
This syntax program is intended to provide an application, not readily available, for users in SPSS who are interested in the Pearson product–moment correlation coefficient (r) and r biased adjustment indices such as the Fisher Approximate Unbiased estimator and the Olkin and Pratt adjustment.
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data,
2017
Universiti Putra Malaysia, Seri Kembangan, Malaysia
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar
Journal of Modern Applied Statistical Methods
The log logistic model with doubly interval censored data is examined. Three methods of constructing confidence interval estimates for the parameter of the model were compared and discussed. The results of the coverage probability study indicated that the Wald outperformed the likelihood ratio and jackknife inferential procedures.
On Poisson Quasi-Lindley Distribution And Its Applications,
2017
Badji-Mokhtar University, Annaba, Algeria
On Poisson Quasi-Lindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi
Journal of Modern Applied Statistical Methods
This paper proposes a recent version of compound Poisson distributions named the Poisson quasi-Lindley (PQL) distribution by compounding Poisson and quasi-Lindley distributions. Some properties of the distributions are given with estimation and some illustrative examples.
Detection Of Outliers In Univariate Circular Data Using Robust Circular Distance,
2017
University Putra Malaysia, Serdang, Malaysia
Detection Of Outliers In Univariate Circular Data Using Robust Circular Distance, Ehab A. Mahmood, Sohel Rana, Habshah Midi, Abdul Ghapor Hussin
Journal of Modern Applied Statistical Methods
A robust statistic to detect single and multi-outliers in univariate circular data is proposed. The performance of the proposed statistic was tested by applying it to a simulation study and to three real data sets, and was demonstrated to be robust.
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas,
2017
Boston University
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson
Journal of Modern Applied Statistical Methods
Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently large-scale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in large-scale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies.
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab),
2017
Manisa Celal Bayar University, Manisa, Turkey
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç
Journal of Modern Applied Statistical Methods
The main purpose of this study is to review calculation algorithms for some of the most common non-parametric and omnibus tests for normality, and to provide them as a compiled MATLAB function. All tests are coded to provide p-values for those normality tests, and the proposed function gives the results as an output table.
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression,
2017
University of British Columbia
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
A series of simulation studies are reported that investigated the impact of a skewed predictor(s) on the Type I error rate and power of the Wald test in a logistic regression model. Five simulations were conducted for three different regression models. A detailed description of the impact of skewed cell predictor probabilities and sample size provide guidelines for practitioners wherein to expect the greatest problems.
Jmasm 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R),
2017
Wayne State University
Jmasm 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
A web-based Shiny application written in R statistical language was developed and deployed online to calculate a new two dependent samples maximum test as presented in Maggio and Sawilowsky (2014b). The maximum test allows researchers to conduct both the dependent samples t-test and Wilcoxon signed-ranks tests on same data without raising concerns associated with Type I error inflation and choice of statistical tests (Maggio and Sawilowsky, 2014a). The maximum test in R statistical language provides a friendly user interface.
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas),
2017
University of South Florida, Tampa, FL
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas), Isaac Li, Yi-Hsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey
Journal of Modern Applied Statistical Methods
Variance homogeneity (HOV) is a critical assumption for ANOVA whose violation may lead to perturbations in Type I error rates. Minimal consensus exists on selecting an appropriate test. This SAS macro implements 14 different HOV approaches in one-way ANOVA. Examples are given and practical issues discussed.
A Remark For The Admissibility Of Rao’S U-Test,
2017
Northeast Normal University, Changchun, Jilin, China
A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai
Journal of Modern Applied Statistical Methods
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