JASP Reference

Q: Does the reference cover Bayesian regression in JASP?

Yes. The Bayesian regression entry covers Bayesian Adaptive Sampling (BAS), model priors (Uniform, Beta-Binomial), coefficient priors (JZS default), variable inclusion probabilities, posterior coefficient summaries, and model comparison using Bayes Factors. This allows comparison of all possible predictor combinations.

Q: What factor analysis methods are included?

The reference covers Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA) with extraction methods (ML, ULS, PA) and rotation methods (Varimax, Oblimin, Promax), and Confirmatory Factor Analysis (CFA) with model fit indices including CFI, TLI, RMSEA, and SRMR.

Q: Is the SEM module covered?

Yes. The SEM entry covers path analysis, confirmatory factor analysis, and full structural equation modeling using lavaan syntax that can be entered directly in JASP. It includes fit indices (Chi-square, CFI, RMSEA, SRMR) and automatic path diagram generation.

Q: What machine learning capabilities does JASP offer?

JASP provides classification (KNN, LDA, Random Forest, Boosting, SVM), regression (KNN, Random Forest, Boosting), and clustering (K-Means, Fuzzy C-Means, Hierarchical, Model-based). The reference notes cross-validation and confusion matrix outputs for model evaluation.

Q: Can JASP show the underlying R code?

Yes. Under Preferences > Advanced > R syntax, JASP displays the jaspResults-based R code for each analysis. This feature is useful for learning R through GUI-to-code translation and for reproducing JASP analyses in R directly.

Free reference guide: JASP Reference

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About JASP Reference

The JASP Reference is a searchable cheat sheet for JASP statistical software, covering both Bayesian and frequentist analysis modules. Bayesian entries include Bayesian t-tests, Bayesian ANOVA with model comparison, Bayesian regression (BAS with JZS priors), Bayesian correlation, Bayesian contingency tables, and the Jeffreys Bayes Factor interpretation scale (BF10 from anecdotal to extreme evidence).

Frequentist sections cover descriptive statistics, t-tests (independent, paired, one-sample), ANOVA (one-way, repeated measures, ANCOVA, MANOVA), linear and logistic regression, frequencies and contingency tables, reliability analysis (Cronbach alpha, McDonald omega), factor analysis (PCA, EFA, CFA), nonparametric tests, SEM (lavaan-based), meta-analysis, network analysis, and machine learning (classification, regression, clustering).

Designed for researchers, graduate students, and data analysts who use JASP for statistical analysis and need quick reference to Bayes Factor thresholds, prior width settings, effect size measures, post-hoc tests, model fit indices, data import formats, result export options, and R code viewing capabilities.

Key Features

Bayesian t-tests, ANOVA, regression, and correlation with Bayes Factor (BF10) output and prior settings
Jeffreys Bayes Factor interpretation scale from anecdotal (1-3) to extreme (>100) evidence
Frequentist t-tests, ANOVA, and regression with effect sizes (Cohen d, eta-squared, omega-squared)
Factor analysis covering PCA, EFA (ML, ULS, PA extraction; Varimax, Oblimin rotation), and CFA fit indices
SEM module reference with lavaan syntax, path analysis, CFA, and fit indices (CFI, RMSEA, SRMR)
Meta-analysis with forest/funnel plots, publication bias testing (Egger), and heterogeneity measures (I-squared)
Machine learning modules for classification (KNN, LDA, Random Forest, SVM) and clustering (K-Means, hierarchical)
Data import formats (CSV, SPSS, Stata, SAS, R, Excel), .jasp file reproducibility, and R code export

Frequently Asked Questions

What statistical methods does the JASP reference cover?

It covers three categories: Basic Usage (data import, variable types, .jasp files, result export, R code viewing), Frequentist (descriptives, t-tests, ANOVA, regression, frequencies, reliability, factor analysis, nonparametric tests, SEM, meta-analysis, network analysis, machine learning), and Bayesian (Bayesian t-tests, ANOVA, regression, correlation, contingency tables, and Bayes Factor interpretation).

How is the Bayes Factor interpreted in JASP?

The reference includes the Jeffreys interpretation scale: BF10 of 1-3 is anecdotal evidence, 3-10 is moderate, 10-30 is strong, 30-100 is very strong, and >100 is extreme evidence for the alternative hypothesis. BF10 < 1 supports the null hypothesis. The reciprocal 1/BF10 = BF01 gives evidence for the null.

Does the reference cover Bayesian regression in JASP?

Yes. The Bayesian regression entry covers Bayesian Adaptive Sampling (BAS), model priors (Uniform, Beta-Binomial), coefficient priors (JZS default), variable inclusion probabilities, posterior coefficient summaries, and model comparison using Bayes Factors. This allows comparison of all possible predictor combinations.

What factor analysis methods are included?

The reference covers Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA) with extraction methods (ML, ULS, PA) and rotation methods (Varimax, Oblimin, Promax), and Confirmatory Factor Analysis (CFA) with model fit indices including CFI, TLI, RMSEA, and SRMR.

Is the SEM module covered?

Yes. The SEM entry covers path analysis, confirmatory factor analysis, and full structural equation modeling using lavaan syntax that can be entered directly in JASP. It includes fit indices (Chi-square, CFI, RMSEA, SRMR) and automatic path diagram generation.

What machine learning capabilities does JASP offer?

JASP provides classification (KNN, LDA, Random Forest, Boosting, SVM), regression (KNN, Random Forest, Boosting), and clustering (K-Means, Fuzzy C-Means, Hierarchical, Model-based). The reference notes cross-validation and confusion matrix outputs for model evaluation.

Can JASP show the underlying R code?

Yes. Under Preferences > Advanced > R syntax, JASP displays the jaspResults-based R code for each analysis. This feature is useful for learning R through GUI-to-code translation and for reproducing JASP analyses in R directly.

Is this JASP reference free to use?

Yes, it is completely free with no registration required. All content runs in your browser with no data sent to servers. It is part of liminfo.com's collection of free statistical and research tools.