Open Access. Powered by Scholars. Published by Universities.®

Statistical Theory Commons

Open Access. Powered by Scholars. Published by Universities.®

1565 Full-Text Articles 1816 Authors 323634 Downloads 38 Institutions

All Articles in Statistical Theory

Faceted Search

1565 full-text articles. Page 1 of 36.

Propensity Score Analysis With Matching Weights, Liang Li 2017 Cleveland Clinic

Propensity Score Analysis With Matching Weights, Liang Li

Liang Li

The propensity score analysis is one of the most widely used methods for studying the causal treatment effect in observational studies. This paper studies treatment effect estimation with the method of matching weights. This method resembles propensity score matching but offers a number of new features including efficient estimation, rigorous variance calculation, simple asymptotics, statistical tests of balance, clearly identified target population with optimal sampling property, and no need for choosing matching algorithm and caliper size. In addition, we propose the mirror histogram as a useful tool for graphically displaying balance. The method also shares some features of the inverse ...


Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons 2017 Chapman University

Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons

Student Research Day Abstracts and Posters

After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.

I created a dataset of qualitative and quantitative outcomes from my ...


A Distribution Of The First Order Statistic When The Sample Size Is Random, Vincent Z. Forgo Mr 2017 East Tennessee State University

A Distribution Of The First Order Statistic When The Sample Size Is Random, Vincent Z. Forgo Mr

Electronic Theses and Dissertations

Statistical distributions also known as probability distributions are used to model a random experiment. Probability distributions consist of probability density functions (pdf) and cumulative density functions (cdf). Probability distributions are widely used in the area of engineering, actuarial science, computer science, biological science, physics, and other applicable areas of study. Statistics are used to draw conclusions about the population through probability models. Sample statistics such as the minimum, first quartile, median, third quartile, and maximum, referred to as the five-number summary, are examples of order statistics. The minimum and maximum observations are important in extreme value theory. This paper will ...


Limitations In The Systematic Analysis Of Structural Equation Model Fit Indices, Sarah A. Rose, Barry Markman, Shlomo Sawilowsky 2017 Wayne State University

Limitations In The Systematic Analysis Of Structural Equation Model Fit Indices, Sarah A. Rose, Barry Markman, Shlomo Sawilowsky

Journal of Modern Applied Statistical Methods

The purpose of this study was to evaluate the sensitivity of selected fit index statistics in determining model fit in structural equation modeling (SEM). The results indicated a large dependency on correlation magnitude of the input correlation matrix, with mixed results when the correlation magnitudes were low and a primary indication of good model fit. This was due to the default SEM method of Maximum Likelihood that assumes unstandardized correlation values. However, this warning is not well-known, and is only obscurely mentioned in some textbooks. Many SEM computer software programs do not give appropriate error indications that the results are ...


Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi 2017 University of Colombo, Sri Lanka

Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi

Journal of Modern Applied Statistical Methods

The emerging role of modeling multivariate multilevel data in the context of analyzing the risk factors are examined for the severity of cardiovascular disease diabetes, and chronic respiratory conditions. The modeling phase results leads to some important interaction terms between blood glucose, blood pressure, obesity, smoking and alcohol to the mortality rates.


A New Estimator For The Pickands Dependence Function, Marta Ferreira 2017 Centre of Mathematics of the University of Minho, Braga, Portugal

A New Estimator For The Pickands Dependence Function, Marta Ferreira

Journal of Modern Applied Statistical Methods

The Pickands dependence function characterizes an extreme value copula, a useful tool in the modeling of multivariate extremes. A new estimator is presented along with its convergence properties and performance through simulation.


Methodology For Constructing Perceptual Maps Incorporating Measuring Error In Sensory Acceptance Tests, Elisa Norberto Ferreira Santos, Gilberto Rodrigues Liska, Marcelo Angelo Cirillo 2017 Federal University of Triângulo Mineiro, Uberaba, Brazil

Methodology For Constructing Perceptual Maps Incorporating Measuring Error In Sensory Acceptance Tests, Elisa Norberto Ferreira Santos, Gilberto Rodrigues Liska, Marcelo Angelo Cirillo

Journal of Modern Applied Statistical Methods

A new method is proposed based on construction of perceptual maps using techniques of correspondence analysis and interval algebra that allow specifying the measurement error expected in panel choices in the evaluation form described in unstructured 9-point hedonic scale.


The Double Prior Selection For The Parameter Of Exponential Life Time Model Under Type Ii Censoring, Ronak M. Patel, Achyut C. Patel 2017 Som-Lalit College of Commerce, Ahmedabad

The Double Prior Selection For The Parameter Of Exponential Life Time Model Under Type Ii Censoring, Ronak M. Patel, Achyut C. Patel

Journal of Modern Applied Statistical Methods

A comparison of double informative priors assumed for the parameter of exponential life time model is considered. Three different sets of double priors are included, and the results are compared with a forth single prior. The data is Type II censored and Bayes estimators for the parameter and reliability are carried out under a squared error loss function in the cases of the four different sets of prior distributions. The predictive distribution was derived for future failure time and also for the remaining ordered failure times after the first r failure times have been observed. Corresponding Bayes credible equal tail ...


Plant Leaf Image Detection Method Using A Midpoint Circle Algorithm For Shape-Based Feature Extraction, B. Vijaya Lakshmi, V. Mohan 2017 K.L.N. College of Engineering, Tamil Nadu, India

Plant Leaf Image Detection Method Using A Midpoint Circle Algorithm For Shape-Based Feature Extraction, B. Vijaya Lakshmi, V. Mohan

Journal of Modern Applied Statistical Methods

Shape-based feature extraction in content-based image retrieval is an important research area at present. An algorithm is presented, based on shape features, to enhance the set of features useful in a leaf identification system.


A Reinterpretation And Extension Of Mcnemar’S Test, Chauncey M. Dayton 2017 University of Maryland, College Park and BDS Data Analytics, LLC

A Reinterpretation And Extension Of Mcnemar’S Test, Chauncey M. Dayton

Journal of Modern Applied Statistical Methods

The McNemar test is extended to multiple groups based on a latent class model incorporating classes representing consistent responders and a single latent error rate. The method is illustrated with data from a CDC survey of immunizations for flu and pneumonia for which a part-heterogeneous model is selected for interpretation.


Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo 2017 University of Kansas Medical Center

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.


Vol. 16, No. 1 (Full Issue), JMASM Editors 2017 Wayne State University

Vol. 16, No. 1 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

.


Experiment-Wise Type I Error Rates In Nested (Hierarchical) Study Designs, Jack Sawilowsky, Barry Markman 2017 Citigroup

Experiment-Wise Type I Error Rates In Nested (Hierarchical) Study Designs, Jack Sawilowsky, Barry Markman

Journal of Modern Applied Statistical Methods

When conducting a statistical test one of the initial risks that must be considered is a Type I error, also known as a false positive. The Type I error rate is set by nominal alpha, assuming all underlying conditions of the statistic are met. Experiment-wise Type I error inflation occurs when multiple tests are conducted overall for a single experiment. There is a growing trend in the social and behavioral sciences utilizing nested designs. A Monte Carlo study was conducted using a two-layer design. Five theoretical distributions and four real datasets taken from Micceri (1989) were used, each with five ...


Robust Ancova: Confidence Intervals That Have Some Specified Simultaneous Probability Coverage When There Is Curvature And Two Covariates, Rand Wilcox 2017 University of Southern California

Robust Ancova: Confidence Intervals That Have Some Specified Simultaneous Probability Coverage When There Is Curvature And Two Covariates, Rand Wilcox

Journal of Modern Applied Statistical Methods

Consider the commonly occurring situation where the goal is to compare two independent groups and there are two covariates. Let Mj(X) be some conditional measure of location for the jth group associated with some random variable Y given X = (X1, X2). The goal is to H0: M1(X) = M2(X) for each X Ω in a manner that controls the probability of one or more Type I errors. An extant technique (method M1 here) addresses this goal without making any parametric assumption about Mj(X). However, a practical concern is that it does not provide enough detail regarding where ...


Test Statistics For The Comparison Of Means For Two Samples That Include Both Paired And Independent Observations, Ben Derrick, Bethan Russ, Deirdre Toher, Paul White 2017 University of the West of England

Test Statistics For The Comparison Of Means For Two Samples That Include Both Paired And Independent Observations, Ben Derrick, Bethan Russ, Deirdre Toher, Paul White

Journal of Modern Applied Statistical Methods

Standard approaches for analyzing the difference in two means, where partially overlapping samples are present, are less than desirable. Here are introduced two test statistics, making reference to the t-distribution. It is shown that these test statistics are Type I error robust, and more powerful than standard tests.


Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe 2017 Concordia University

Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe

Journal of Modern Applied Statistical Methods

The analysis of robust parameter design is discussed via a model incorporating mean-variance relationship which, when ignored as in the classical regression approach, can be problematic. The model is also capable of alleviating the difficulties of the regression approach in the search of the minimum variance occurring region.


Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks 2017 Beijing Foreign Studies University

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.


Robustness And Power Comparison Of The Mood-Westenberg And Siegel-Tukey Tests, Linda C. Lowenstein, Shlomo S. Sawilowsky 2017 Wasthington University in St. Louis

Robustness And Power Comparison Of The Mood-Westenberg And Siegel-Tukey Tests, Linda C. Lowenstein, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The Mood-Westenberg and Siegel-Tukey tests were examined to determine their robustness with respect to Type-I error for detecting variance changes when their assumptions of equal means were slightly violated, a condition that approaches the Behrens-Fisher problem. Monte Carlo methods were used via 34,606 variations of sample sizes, α levels, distributions/data sets, treatments modeled as a change in scale, and treatments modeled as a shift in means. The Siegel-Tukey was the more robust, and was able to handle a more diverse set of conditions.


A New Estimator Based On Auxiliary Information Through Quantitative Randomized Response Techniques, Nilgün Özgül, Hülya Çıngı 2017 Hacettepe University

A New Estimator Based On Auxiliary Information Through Quantitative Randomized Response Techniques, Nilgün Özgül, Hülya Çıngı

Journal of Modern Applied Statistical Methods

An exponential-type estimator is developed for the population mean of the sensitive study variable based on various Randomized Response Techniques (RRT) using a non-sensitive auxiliary variable. The mean squared error (MSE) of the proposed estimator is derived for generalized RRT models. The proposed estimator is compared with competitors in a simulation study and an application. The proposed estimator is found to be more efficient using a non-sensitive auxiliary variable.


Control Charts For Mean For Non-Normally Correlated Data, J. R. Singh, Ab Latif Dar 2017 Vikram University, Ujjain, India

Control Charts For Mean For Non-Normally Correlated Data, J. R. Singh, Ab Latif Dar

Journal of Modern Applied Statistical Methods

Traditionally, quality control methodology is based on the assumption that serially-generated data are independent and normally distributed. On the basis of these assumptions the operating characteristic (OC) function of the control chart is derived after setting the control limits. But in practice, many of the basic industrial variables do not satisfy both the assumptions and hence one may doubt the validity of the inferences drawn from the control charts. In this paper the power of the control chart for the mean is examined when both the assumptions of independence and normality are not tenable. The OC function is calculated and ...


Digital Commons powered by bepress