Journal of Modern Applied Statistical Methods

Aims & Scope

The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.

Work appearing in Regular Articles, Brief Reports, and Emerging Scholars are externally peer reviewed, with input from the Editorial Board; in Statistical Software Applications and Review and JMASM Algorithms and Code are internally reviewed by the Editorial Board.

Three areas are appropriate for JMASM: Development or study of new statistical tests or procedures, or the comparison of existing statistical tests or procedures, using computer-intensive Monte Carlo, bootstrap, jackknife, or resampling methods Development or study of nonparametric, robust, permutation, exact, and approximate randomization methods Applications of computer programming, preferably in Fortran (all other programming environments are welcome), related to statistical algorithms, pseudo-random number generators, simulation techniques, and self-contained executable code to carry out new or interesting statistical methods.

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Decision Sciences and Mathematics, designed to support cutting-edge academic discovery.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• New Effect Size Rules of Thumb

  Citation: 2358

  Authors: Shlomo S.

• Ordinal Versions of Coefficients Alpha and Theta for Likert Rating Scales

  Citation: 722

  Authors: Bruno D., Anne M., Cornelia

• Comparison of Model Fit Indices Used in Structural Equation Modeling Under Multivariate Normality

  Citation: 425

  Authors: Sengul, Ilker

• Beta-Weibull Distribution: Some Properties and Applications to Censored Data

  Citation: 187

  Authors: Carl, Felix, Olugbenga

• Some General Guidelines for Choosing Missing Data Handling Methods in Educational Research

  Citation: 178

  Authors: Jehanzeb R

• JMASM9: Converting Kendall's Tau For Correlational Or Meta-Analytic Analyses

  Citation: 159

  Authors: David A.

• Determining Parallel Analysis Criteria

  Citation: 134

  Authors: Marley W.

• Impact of Rank-Based Normalizing Transformations on the Accuracy of Test Scores

  Citation: 122

  Authors: Shira R., Shlomo S.

• The Q-Sort Method: Assessing Reliability And Construct Validity Of Questionnaire Items At A Pre-Testing Stage

  Citation: 122

  Authors: Abraham Y., S. Subba, Luis E., T. S.

• Recommended Sample Size for Conducting Exploratory Factor Analysis on Dichotomous Data

  Citation: 104

  Authors: Robert H., Daniel J.