A new, open-source engine for meta-analysis: free for everyone, and built to work wherever you do research.
Free and open source. No accounts, no tokens, no paid plans. The code is open, the methods are documented, and every result can be reproduced.
A more capable statistical engine. Pairwise and single-group analyses (including prevalence), modern heterogeneity estimators and Hartung–Knapp inference, subgroups, meta-regression, and sensitivity diagnostics. In development: multilevel models for dependent effects, network meta-analysis, and umbrella reviews.
Use it your way. In the Meta-Mar web hub, directly through the API, or inside your own AI assistant, such as Claude, with Meta-Mar tools and skills: the AI explains, Meta-Mar computes. Run it locally, and your data never leaves your machine.
Until then, the current Meta-Mar stays free and available.
Meta-Mar Classic is a free-to-use platform for quantitative evidence synthesis.
It provides an interactive environment for meta-analysis of continuous, binary, correlation, and pre-calculated effect-size data. Analyses include fixed- and random-effects models, heterogeneity assessment, publication-bias diagnostics, sensitivity analysis, subgroup analysis, meta-regression, and interactive visualisations.
Statistical analyses are performed by a validated R-based analysis engine and are accessible through the web interface without installation, registration, or payment.
Meta-Mar is developed as scientific software for research, teaching, and reproducible evidence synthesis.
Workshop in evidence synthesis — Department of Nursing, Faculty of Nursing and Occupational Therapy, University of Extremadura, Cáceres (May 2026)
20 participants completing 5–6 individual meta-analyses each across a three-day course on Synthesis of Evidence in Health Sciences II.
PhD course in meta-analysis — Center for Health Technology Assessment, Semmelweis University, Budapest (January 2026)
~30 concurrent users running real-time analyses with AI guidance tailored to each study.
Meta-Mar Workshop: End-to-end meta-analysis tutorials using real clinical data (e.g., MIMIC-IV). From study design and cohort extraction to statistical analysis and AI-generated interpretation.
Coming soon.
Effective date: 11 November 2026
This policy covers www.meta-mar.com and Meta-Mar Classic, the current analysis application. Meta-Mar is free to use. It needs no account and no payment, and it does not use analytics or advertising trackers.
Ashkan Beheshti Hamedani
c/o Philipps-Universität Marburg, Fachbereich Psychologie, AG Klinische Kinder- und Jugendpsychologie
Gutenbergstr. 18, 35037 Marburg, Germany
Email: ashkan.beheshti@staff.uni-marburg.de
See also the Impressum.
There are none. Google Analytics and similar tools have been removed.
The survey on the Contribute page stores only which priorities were ticked and a timestamp. It stores no name, email address or IP address, and it can be answered anonymously. Aggregated counts are public on the survey-results page. The counts are held in a managed database service (Supabase).
Under the GDPR you have the right of access, rectification, erasure, restriction of processing, data portability and objection (Arts. 15–21), and the right to withdraw consent at any time. Because Classic holds no account data, we can usually identify you in our systems only if you give us specifics (for example the time of a request). You also have the right to lodge a complaint with a supervisory authority, in particular in the EU member state where you live or work or where an alleged infringement took place. The authority responsible for the controller is the Hessian Commissioner for Data Protection and Freedom of Information (Der Hessische Beauftragte für Datenschutz und Informationsfreiheit), Wiesbaden.
The Meta-Mar 5 engine is designed to be stateless: requests are computed and not stored. It will also run locally on your own computer or institutional server, so your data never has to leave your machine.
For privacy questions or requests, contact: ashkan.beheshti@staff.uni-marburg.de
Ashkan Beheshti Hamedani
c/o Philipps-Universität Marburg
Fachbereich Psychologie, AG Klinische Kinder- und Jugendpsychologie
Gutenbergstr. 18
35037 Marburg
Germany
Email: ashkan.beheshti@staff.uni-marburg.de
Meta-Mar is a free academic software project for meta-analysis, developed and maintained by Ashkan Beheshti Hamedani.
Source code: AGPL-3.0 (see the LICENSE file in each repository). Website texts and documentation: CC BY 4.0 (see CONTENT-LICENSE). © 2020–2026 Ashkan Beheshti.
See also the Privacy Policy.
Help shape the platform's future through feedback and community engagement.
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If you use Meta-Mar in your research, please cite the preprint and/or the software as appropriate.
Beheshti, A., Sazmand, H., Chavanon, M.-L., & Christiansen, H. (2026). Meta-Mar: An AI-assisted web platform for accessible and rigorous meta-analysis. OSF Preprints. https://doi.org/10.31222/osf.io/psw4x_v1
@software{beheshti2026metamar,
author = {Beheshti, Ashkan and Sazmand, Hassan and Chavanon, Mira-Lynn and Christiansen, Hanna},
title = {Meta-Mar: An AI-Integrated Web Platform for Meta-Analysis},
year = {2026},
url = {https://www.meta-mar.com},
version = {4.0.2}
}
Software paper under review at the Journal of Open Source Software (JOSS).