JASP

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JASP
JASP logo.svg
Stable release
0.9.1 / October 11, 2018 (2018-10-11)
Repository JASP Github page
Written in C++, R, JavaScript
Operating system Microsoft Windows, Mac OS X and Linux
Type Statistics
License GNU Affero General Public License
Website jasp-stats.org

JASP is a free and open-source graphical program for statistical analysis, designed to be easy to use, and familiar to users of SPSS. Additionally, it provides many Bayesian statistical methods.[1][2] JASP generally produces APA style results tables and plots to ease publication. It promotes open science by integration with the Open Science Framework and reproducibility by integrating the analysis settings into the results. The development of JASP is financially supported by several universities and research funds.

JASP screenshot

Analyses[edit]

JASP offers frequentist inference and Bayesian inference on the same statistical models. Frequentist inference uses p-values and confidence intervals to control error rates in the limit of infinite perfect replications. Bayesian inference uses credible intervals and Bayes factors[3] to estimate credible parameter values and model evidence given the available data and prior knowledge.

The following analyses are available in JASP:

Analysis Frequentist Bayesian
T-tests: independent, paired, one-sample ☑Y ☑Y
Mann-Whitney U and Wilcoxon ☑Y ☑Y
Correlation:[4] Pearson, Spearman, and Kendall ☑Y ☑Y
Reliability analyses: α, γδ, and ω ☑Y
ANOVA, ANCOVA, and Repeated measures ANOVA ☑Y ☑Y
Linear regression ☑Y ☑Y
Log-linear regression ☑Y ☑Y
Logistic regression ☑Y
Contingency tables (including Chi-squared test) ☑Y ☑Y
Binomial test ☑Y ☑Y
Multinomial test ☑Y
Exploratory factor analysis (EFA) ☑Y
Principal component analysis (PCA) ☑Y
Structural equation modeling (SEM) ☑Y
Network Analysis ☑Y
Meta Analysis ☑Y
Summary Stats[5] ☑Y

Other features[edit]

  • Descriptive statistics and plots.
  • Assumption checks for all analyses, including Levene's test, the Shapiro–Wilk test, and Q–Q plot.
  • Imports SPSS files, comma-separated files, and Microsoft Excel files.
  • Open Science Framework integration.
  • Bayesian inference from frequentist summary statistics for t-test, regression, and binomial tests. This is offered through the Summary Statistics module.
  • Data filtering: Use either R code or a drag-and-drop GUI to select cases of interest.
  • Export tables from JASP in LaTeX format.

References[edit]

  1. ^ Wagenmakers EJ, Love J, Marsman M, Jamil T, Ly A, Verhagen J, et al. (February 2018). "Bayesian inference for psychology. Part II: Example applications with JASP". Psychonomic Bulletin & Review. 25 (1): 58–76. doi:10.3758/s13423-017-1323-7. PMC 5862926. PMID 28685272.
  2. ^ Love J, Selker R, Verhagen J, Marsman M, Gronau QF, Jamil T, Smira M, Epskamp S, Wil A, Ly A, Matzke D, Wagenmakers EJ, Morey MD, Rouder JN (2015). "Software to Sharpen Your Stats". APS Observer. 28 (3).
  3. ^ Quintana DS, Williams DR (June 2018). "Bayesian alternatives for common null-hypothesis significance tests in psychiatry: a non-technical guide using JASP". BMC Psychiatry. 18 (1): 178. doi:10.1186/s12888-018-1761-4. PMC 5991426. PMID 29879931.
  4. ^ Nuzzo RL (December 2017). "An Introduction to Bayesian Data Analysis for Correlations". PM&R. 9 (12): 1278–1282. doi:10.1016/j.pmrj.2017.11.003.
  5. ^ Ly A, Raj A, Etz A, Marsman M, Gronau QF, Wagenmakers E (2017-05-30). "Bayesian Reanalyses from Summary Statistics: A Guide for Academic Consumers". Open Science Framework.

External links[edit]