JASP

🧱 Overpromised Accessibility, Underdelivered Depth

JASP markets itself as a user-friendly GUI for statistical analysis, but this ease of use comes at the cost of limited methodological depth and flexibility.

πŸ” Limited Statistical and Meta-Analytic Features

πŸ€– No Integration with Automation or Data Extraction Tools

πŸ“‰ Reproducibility and Transparency Issues

⚠️ Accessibility vs. Professionalism Trade-Off

🧨 Final Verdict

JASP is a convenient tool for introductory statistics and teaching, but it is unsuitable for complex, high-stakes meta-analyses or advanced research. Its simplistic interface, limited features, and poor integration hinder rigorous evidence synthesis and reproducibility.

Recommendation: Use JASP for learning or exploratory data analysis only. For robust meta-analytic work, prefer more flexible and transparent tools like R packages or advanced workflow platforms.

Better Alternatives to JASP

πŸ₯‡ R with Meta-Analysis Packages (metafor, meta, netmeta)

Greater control, transparency, and methodological sophistication

πŸ” Comprehensive Meta-Analysis (CMA)

More focused and feature-rich for meta-analytic purposes

πŸ€– AI-Augmented Tools: Elicit + RobotReviewer

Streamlines upstream review tasks typically manual in JASP workflows

πŸ”§ Systematic Review Platforms: Covidence, DistillerSR

Supports entire review lifecycle, not just statistical analysis

πŸ“Š Summary Table

Tool Strengths Why Better Than JASP
R (metafor, meta, netmeta) Advanced scripting, flexibility, reproducibility Maximum control and transparency
Comprehensive Meta-Analysis GUI with rich meta-analytic features More advanced and focused than JASP
Elicit + RobotReviewer AI-assisted extraction and bias assessment Automates and accelerates manual processes
Covidence / DistillerSR Full systematic review management Manages complete SR workflow collaboratively

🧠 Final Recommendation