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Applied Statistics

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Full-Text Articles in Social and Behavioral Sciences

The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin Jul 2020

The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin

Journal of Modern Applied Statistical Methods

The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.


Bayesian Estimation Of The Parameters Of Discrete Weibull Type (I) Distribution, Samir Kamel Ashour, Mohamed Salem Abdelwahab Muiftah Jul 2020

Bayesian Estimation Of The Parameters Of Discrete Weibull Type (I) Distribution, Samir Kamel Ashour, Mohamed Salem Abdelwahab Muiftah

Journal of Modern Applied Statistical Methods

Bayesian estimation of the continuous Weibull distribution parameters was studied by Ahmad and Ahmad (2013) under the assumption of knowing the shape parameter. Bayesian estimates are considered here of the parameters of the discrete Weibull Type I [DW(I)] distribution and are obtained under two different assumptions: when the shape parameter is known, and when both parameters are independent random variables. A Mathcad program is performed to simulate data from the DW(I) distribution considering different values of the parameters and different sample sizes, and to obtain Bayesian parameter estimates. The resulted estimates are compared to the ML and proportion estimates obtained …


The Logic Model, Participatory Evaluation And Out Of School Art Programs, Kimberly A. Kleinhans Jul 2020

The Logic Model, Participatory Evaluation And Out Of School Art Programs, Kimberly A. Kleinhans

Journal of Modern Applied Statistical Methods

The logic model and participatory evaluation are two popular methods of conducting program evaluation. Although both methods have their strengths, each has distinct weaknesses which can be ameliorated by combining them both together. The combined method is used to evaluate an out of school art program at a museum. Using both the logic model and participatory evaluation yielded beneficial results with more accurate representation of program outcomes.


Empirical Comparison Of Tests For One-Factor Anova Under Heterogeneity And Non-Normality: A Monte Carlo Study, Diep Nguyen, Eunsook Kim, Yan Wang, Thanh Vinh Pham, Yi-Hsin Chen, Jeffrey D. Kromrey Jul 2020

Empirical Comparison Of Tests For One-Factor Anova Under Heterogeneity And Non-Normality: A Monte Carlo Study, Diep Nguyen, Eunsook Kim, Yan Wang, Thanh Vinh Pham, Yi-Hsin Chen, Jeffrey D. Kromrey

Journal of Modern Applied Statistical Methods

Although the Analysis of Variance (ANOVA) F test is one of the most popular statistical tools to compare group means, it is sensitive to violations of the homogeneity of variance (HOV) assumption. This simulation study examines the performance of thirteen tests in one-factor ANOVA models in terms of their Type I error rate and statistical power under numerous (82,080) conditions. The results show that when HOV was satisfied, the ANOVA F or the Brown-Forsythe test outperformed the other methods in terms of both Type I error control and statistical power even under non-normality. When HOV was violated, the Structured Means …


A Generalized Family Of Lifetime Distributions And Survival Models, Mahmoud Aldeni, Felix Famoye, Carl Lee Jul 2020

A Generalized Family Of Lifetime Distributions And Survival Models, Mahmoud Aldeni, Felix Famoye, Carl Lee

Journal of Modern Applied Statistical Methods

In lifetime data, the hazard function is a common technique for describing the characteristics of lifetime distribution. Monotone increasing or decreasing, and unimodal are relatively simple hazard function shapes, which can be modeled by many parametric lifetime distributions. However, fewer distributions are capable of modeling diverse and more complicated shapes such as N-shaped, reflected N-shaped, W-shaped, and M-shaped hazard rate functions. A generalized family of lifetime distributions, the uniform-R{generalized lambda} (U-R{GL}) are introduced and the corresponding survival models are derived, and applied to two lifetime data sets. The survival model is applied to a right censored lifetime data set.


Forward And Backward Continuation Ratio Models For Ordinal Response Variables, Xing Liu, Haiyan Bai Jul 2020

Forward And Backward Continuation Ratio Models For Ordinal Response Variables, Xing Liu, Haiyan Bai

Journal of Modern Applied Statistical Methods

There are different types of continuation ratio (CR) models for ordinal response variables. The different model equations, corresponding parameterizations, and nonequivalent results are confusing. The purpose of this study is to introduce different types of forward and backward CR models, demonstrate how to implement these models using Stata, and compare the results using data from the Educational Longitudinal Study of 2002 (ELS:2002).


A Revised Logic Model For Educational Program Evaluation, Zsa-Zsa Booker Jul 2020

A Revised Logic Model For Educational Program Evaluation, Zsa-Zsa Booker

Journal of Modern Applied Statistical Methods

The logic model is an evaluation tool popularly used for obtaining grant funding. Its limitations make it unlike other theory driven evaluation methods. A critical examination of the logic model leads to the construction of an enriched revised logic model.


Jmasm 52: Extremely Efficient Permutation And Bootstrap Hypothesis Tests Using R, Christina Chatzipantsiou, Marios Dimitriadis, Manos Papadakis, Michail Tsagris Jul 2020

Jmasm 52: Extremely Efficient Permutation And Bootstrap Hypothesis Tests Using R, Christina Chatzipantsiou, Marios Dimitriadis, Manos Papadakis, Michail Tsagris

Journal of Modern Applied Statistical Methods

Re-sampling based statistical tests are known to be computationally heavy, but reliable when small sample sizes are available. Despite their nice theoretical properties not much effort has been put to make them efficient. Computationally efficient method for calculating permutation-based p-values for the Pearson correlation coefficient and two independent samples t-test are proposed. The method is general and can be applied to other similar two sample mean or two mean vectors cases.


Jmasm 53: Miccerird, Michael Lance Jul 2020

Jmasm 53: Miccerird, Michael Lance

Journal of Modern Applied Statistical Methods

Fortran 77 and 90 modules (REALPOPS.lib) exist for invoking the 8 distributions estimated by Micceri (1989). These respective modules were created by Sawilowsky et al. (1990) and Sawilowsky and Fahoome (2003). The MicceriRD (Micceri’s Real Distributions) Python package was created because Python is increasingly used for data analysis and, in some cases, Monte Carlo simulations.


Bayesian Analysis Of Extended Cox Model With Time-Varying Covariates Using Bootstrap Prior, Oyebayo R. Olaniran, Mohd Asrul A. Abdullah Jul 2020

Bayesian Analysis Of Extended Cox Model With Time-Varying Covariates Using Bootstrap Prior, Oyebayo R. Olaniran, Mohd Asrul A. Abdullah

Journal of Modern Applied Statistical Methods

A new Bayesian estimation procedure for extended cox model with time varying covariate was presented. The prior was determined using bootstrapping technique within the framework of parametric empirical Bayes. The efficiency of the proposed method was observed using Monte Carlo simulation of extended Cox model with time varying covariates under varying scenarios. Validity of the proposed method was also ascertained using real life data set of Stanford heart transplant. Comparison of the proposed method with its competitor established appreciable supremacy of the method.


Identifying Which Of J Independent Binomial Distributions Has The Largest Probability Of Success, Rand Wilcox Jul 2020

Identifying Which Of J Independent Binomial Distributions Has The Largest Probability Of Success, Rand Wilcox

Journal of Modern Applied Statistical Methods

Let p1,…, pJ denote the probability of a success for J independent random variables having a binomial distribution and let p(1) ≤ … ≤ p(J) denote these probabilities written in ascending order. The goal is to make a decision about which group has the largest probability of a success, p(J). Let 1,…, J denote estimates of p1,…,pJ, respectively. The strategy is to test J − 1 hypotheses comparing the group with the largest estimate to each of the J − 1 …


Regression: Determining Which Of P Independent Variables Has The Largest Or Smallest Correlation With The Dependent Variable, Plus Results On Ordering The Correlations Winsorized, Rand Wilcox Jul 2020

Regression: Determining Which Of P Independent Variables Has The Largest Or Smallest Correlation With The Dependent Variable, Plus Results On Ordering The Correlations Winsorized, Rand Wilcox

Journal of Modern Applied Statistical Methods

In a regression context, consider p independent variables and a single dependent variable. The paper addresses two goals. The first is to determine the extent it is reasonable to make a decision about whether the largest estimate of the Winsorized correlations corresponds to the independent variable that has the largest population Winsorized correlation. The second is to determine the extent it is reasonable to decide that the order of the estimates of the Winsorized correlations correctly reflects the true ordering. Both goals are addressed by testing relevant hypotheses. Results in Wilcox (in press a) suggest using a multiple comparisons procedure …


Joint Models Of Longitudinal Outcomes And Informative Time, Jangdong Seo Jun 2020

Joint Models Of Longitudinal Outcomes And Informative Time, Jangdong Seo

Journal of Modern Applied Statistical Methods

Longitudinal data analyses commonly assume that time intervals are predetermined and have no information regarding the outcomes. However, there might be irregular time intervals and informative time. Presented are joint models and asymptotic behaviors of the parameter estimates. Also, the models are applied for real data sets.


Comparison Of Scale Identification Methods In Mixture Irt Models, Youn-Jeng Choi, Allan S. Cohen Jun 2020

Comparison Of Scale Identification Methods In Mixture Irt Models, Youn-Jeng Choi, Allan S. Cohen

Journal of Modern Applied Statistical Methods

The effects of three scale identification constraints in mixture IRT models were studied. A simulation study found no constraint effect on the mixture Rasch and mixture 2PL models, but the item anchoring constraint was the only one that worked well on selecting correct model with the mixture 3PL model.


Comparing Means Under Heteroscedasticity And Nonnormality: Further Exploring Robust Means Modeling, Alyssa Counsell, Robert Philip Chalmers, Robert A. Cribbie Jun 2020

Comparing Means Under Heteroscedasticity And Nonnormality: Further Exploring Robust Means Modeling, Alyssa Counsell, Robert Philip Chalmers, Robert A. Cribbie

Journal of Modern Applied Statistical Methods

Comparing the means of independent groups is a concern when the assumptions of normality and variance homogeneity are violated. Robust means modeling (RMM) was proposed as an alternative to ANOVA-type procedures when the assumptions of normality and variance homogeneity are violated. The purpose of this study is to compare the Type I error and power rates of RMM to the trimmed Welch procedure. A Monte Carlo study was used to investigate RMM and the trimmed Welch procedure under several conditions of nonnormality and variance heterogeneity. The results suggest that the trimmed Welch provides a better balance of Type I error …


Inferences About The Probability Of Success, Given The Value Of A Covariate, Using A Nonparametric Smoother, Rand Wilcox Jun 2020

Inferences About The Probability Of Success, Given The Value Of A Covariate, Using A Nonparametric Smoother, Rand Wilcox

Journal of Modern Applied Statistical Methods

For a binary random variable Y, let p(x) = P(Y = 1 | X = x) for some covariate X. The goal of computing a confidence interval for p(x) is considered. In the logistic regression model, even a slight departure difficult to detect via a goodness-of-fit test can yield inaccurate results. The accuracy of a confidence interval can deteriorate as the sample size increases. The goal is to suggest an alternative approach based on a smoother, which provides a more flexible approximation of p(x).


A Note On Inferences About The Probability Of Success, Rand Wilcox Jun 2020

A Note On Inferences About The Probability Of Success, Rand Wilcox

Journal of Modern Applied Statistical Methods

There is an extensive literature dealing with inferences about the probability of success. A minor goal in this note is to point out when certain recommended methods can be unsatisfactory when the sample size is small. The main goal is to report results on the two-sample case. Extant results suggest using one of four methods. The results indicate when computing a 0.95 confidence interval, two of these methods can be more satisfactory when dealing with small sample sizes.


On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix May 2020

On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix

Journal of Modern Applied Statistical Methods

Discriminant function coefficients are useful for describing group differences and identifying variables that distinguish between groups. Test procedures were compared based on asymptotically approximations, empirical, and exact distributions for testing hypotheses about discriminant function coefficients. These tests are useful for assessing variable importance in multivariate group designs.


A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters, Housila P. Singh, Anita Yadav May 2020

A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters, Housila P. Singh, Anita Yadav

Journal of Modern Applied Statistical Methods

Classes of ratio-type estimators t (say) and ratio-type exponential estimators te (say) of the population mean are proposed, and their biases and mean squared errors under large sample approximation are presented. It is the class of ratio-type exponential estimators te provides estimators more efficient than the ratio-type estimators.


Recurrence Relations For Marginal And Joint Moment Generating Functions Of Topp-Leone Generated Exponential Distribution Based On Record Values And Its Characterization, Zaki Anwar, Neetu Gupta, Mohd Akram Raza Khan, Qazi Azhad Jamal May 2020

Recurrence Relations For Marginal And Joint Moment Generating Functions Of Topp-Leone Generated Exponential Distribution Based On Record Values And Its Characterization, Zaki Anwar, Neetu Gupta, Mohd Akram Raza Khan, Qazi Azhad Jamal

Journal of Modern Applied Statistical Methods

The exact expressions and some recurrence relations are derived for marginal and joint moment generating functions of kth lower record values from Topp-Leone Generated (TLG) Exponential distribution. This distribution is characterized by using the recurrence relation of the marginal moment generating function of kth lower record values.


An Improved Two Independent-Samples Randomization Test For Single-Case Ab-Type Intervention Designs: A 20-Year Journey, Joel R. Levin, John M. Ferron, Boris S. Gafurov May 2020

An Improved Two Independent-Samples Randomization Test For Single-Case Ab-Type Intervention Designs: A 20-Year Journey, Joel R. Levin, John M. Ferron, Boris S. Gafurov

Journal of Modern Applied Statistical Methods

Detailed is a 20-year arduous journey to develop a statistically viable two-phase (AB) single-case two independent-samples randomization test procedure. The test is designed to compare the effectiveness of two different interventions that are randomly assigned to cases. In contrast to the unsatisfactory simulation results produced by an earlier proposed randomization test, the present test consistently exhibited acceptable Type I error control under various design and effect-type configurations, while at the same time possessing adequate power to detect moderately sized intervention-difference effects. Selected issues, applications, and a multiple-baseline extension of the two-sample test are discussed.


Support Vector Machine-Based Modified Sp Statistic For Subset Selection With Non-Normal Error Terms, Shivaji Shripati Desai, D N. Kashid May 2020

Support Vector Machine-Based Modified Sp Statistic For Subset Selection With Non-Normal Error Terms, Shivaji Shripati Desai, D N. Kashid

Journal of Modern Applied Statistical Methods

Support vector machine (SVM) is used for estimation of regression parameters to modify the sum of cross products (Sp). It works well for some nonnormal error distributions. The performance of existing robust methods and the modified Sp is evaluated through simulated and real data. The results show the performance of the modified Sp is good.


Logistic Growth Modeling With Markov Chain Monte Carlo Estimation, Jaehwa Choi, Jinsong Chen, Jeffrey R. Harring Apr 2020

Logistic Growth Modeling With Markov Chain Monte Carlo Estimation, Jaehwa Choi, Jinsong Chen, Jeffrey R. Harring

Journal of Modern Applied Statistical Methods

A new growth modeling approach is proposed to can fit inherently nonlinear (i.e., logistic) function without constraint nor reparameterization. A simulation study is employed to investigate the feasibility and performance of a Markov chain Monte Carlo method within Bayesian estimation framework to estimate a fully random version of a logistic growth curve model under manipulated conditions such as the number and timing of measurement occasions and sample sizes.


A Simulation Study On Increasing Capture Periods In Bayesian Closed Population Capture-Recapture Models With Heterogeneity, Ross M. Gosky, Joel Sanqui Apr 2020

A Simulation Study On Increasing Capture Periods In Bayesian Closed Population Capture-Recapture Models With Heterogeneity, Ross M. Gosky, Joel Sanqui

Journal of Modern Applied Statistical Methods

Capture-Recapture models are useful in estimating unknown population sizes. A common modeling challenge for closed population models involves modeling unequal animal catchability in each capture period, referred to as animal heterogeneity. Inference about population size N is dependent on the assumed distribution of animal capture probabilities in the population, and that different models can fit a data set equally well but provide contradictory inferences about N. Three common Bayesian Capture-Recapture heterogeneity models are studied with simulated data to study the prevalence of contradictory inferences is in different population sizes with relatively low capture probabilities, specifically at different numbers of …


An Exploration Of Link Functions Used In Ordinal Regression, Thomas J. Smith, David A. Walker, Cornelius M. Mckenna Apr 2020

An Exploration Of Link Functions Used In Ordinal Regression, Thomas J. Smith, David A. Walker, Cornelius M. Mckenna

Journal of Modern Applied Statistical Methods

The purpose of this study is to examine issues involved with choice of a link function in generalized linear models with ordinal outcomes, including distributional appropriateness, link specificity, and palindromic invariance are discussed and an exemplar analysis provided using the Pew Research Center 25th anniversary of the Web Omnibus Survey data. Simulated data are used to compare the relative palindromic invariance of four distinct indices of determination/discrimination, including a newly proposed index by Smith et al. (2017).


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 Apr 2020

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, Lili Yu, Varadan Sevilimedu, Robert Vogel, Hani Samawi Apr 2020

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, Jennifer E. V. Lloyd, Jacqui Boonstra, Lisa Chen, Barry Forer, Ruth Hershler, Constance Milbrath, Brenda T. Poon, Neda Razaz, Pippa Rowcliffe, Kimberly Schonert-Reichl Apr 2020

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, Moustafa Omar Ahmed Abu-Shawiesh, Aamir Saghir Apr 2020

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, Danjie Zou, Jennifer E. V. Lloyd, Jennifer L. Baumbusch Apr 2020

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.