MetaJam

Meta-analysis for jamovi, powered mainly by the R package meta.

GPL >= 2 DOI 10.5281/zenodo.21226177

Releases

Analyses

Available meta-analysis workflows and the main analysis options in one compact overview.

Available Analyses

Continuous Outcomes: Analyze continuous outcome data using means, standard deviations, and sample sizes for the experimental and control groups.
Binary Outcomes: Analyze binary outcome data using event counts and sample sizes for the experimental and control groups.
Incidence Rate Outcomes: Analyze incidence rate outcome data using event counts and person-time for the experimental and control groups.

Single Means: Analyze single-group data using means, standard deviations, and sample sizes.
Single Proportions: Analyze single-group data using event counts and sample sizes.

Analyze precomputed effect sizes with standard errors or confidence intervals.

Create summary and traffic light plots from risk-of-bias assessments using RoB 2, RoB 2 (cluster), ROBINS-I, ROBINS-E, QUADAS-2, and QUIPS.

Analysis Options

Model Settings: Fit common-effect and random-effects models with various effect measures and heterogeneity estimators.
Subgroup Analysis: Compare effects and test for differences across subgroups.
Meta-Regression: Fit meta-regression models to explore the effect of continuous and categorical predictors.
Leave-One-Out Analysis: Evaluate the influence of individual studies by omitting them one at a time.
Cumulative Meta-Analysis: Examine how the pooled effect changes as studies are added sequentially in a selected order.
Publication Bias: Assess publication bias using funnel plots, trim-and-fill analysis, and the Doi plot / LFK index.

This module is actively being developed. Questions, issues, and feature ideas are welcome.

If MetaJam helps your research or work, cite the module and star the GitHub repository.