Blog and discussions

Our MAER-Net Blog seeks to stimulate discussions about method and insights learned through experience among meta-analysts in economics, business, and the social sciences. We invite all researchers to contribute to this blog by sharing their thoughts about challenges of meta-analysis, recent advances in meta-analysis, or what has been learned thorough recent meta-analysis applications.

We also invite our members to post short summaries of their current research for purposes of discussion. Tomas Havranek and his coauthors have graciously offered to share their paper on the Cobb-Douglas aggregate production function and the advisability of using this simplification. Comments are welcome.

Write a new post or participate in ongoing discussions by adding comments. Every contribution helps to make progress.

All visitors can see existing blogs posts. To comment or to create a new blog post, please use the sign-in/register button and create a new member account. For a quick technical introduction to the blog and its functionalities, please read the post “MAER-Net Blog - Introduction”.

Developing "Guidelines for the Use of AI in Meta-Analysis of Economics Research" (GUAI-MAER) - and - A Solicitation of Feedback

Developing "Guidelines for the Use of AI in Meta-Analysis of Economics Research" (GUAI-MAER) - and - A Solicitation of Feedback Preamble During the Open Forum of the 2025 MAER-Net Colloquium held at the University of Ottawa, a proposal to develop guidelines for the use of AI in meta-analysis of economics research was made. While some members noted that the rapid evolution of AI would preclude an authoritative and static document from offering specific guidance, others noted

Nikolai Cook

Oct 27, 20257 min read

MAER-Net Blog - Introduction

Introduction to the MAER-Net Blog Content overview How to create a new account for the MAER-Net Blog. Access your profile . Subscribe to...

MAER Network

Feb 14, 20191 min read

Building Meta-Analysis Datasets with AI Assistance: A Case Study. PART 1: Using ChatGPT to Assist with Literature Searching

Introduction to this series of blogs This is the first of four blogs on the topic of how AI can assist in assembling datasets for meta-analyses. The four blogs are organized by the following topics: Using ChatGPT to Assist with Literature Searching Using ChatGPT to Assist with Collecting and Organizing Studies Using SysRev for Title and Abstract Screening and Data Extraction Lessons Learned These blogs chronicle my efforts to learn about how AI can assist in the process of s

bob.reed

2 days ago11 min read

Building Meta-Analysis Datasets with AI Assistance: A Case Study. Part 2: Using ChatGPT to Assist with Collecting and Organizing Studies

Introduction In the previous post, I described how I used ChatGPT to help reason through the conceptual structure of a meta-analysis on inflation and subjective well-being and to arrive at a set of Boolean search terms suitable for use across multiple bibliographic databases. That post ended at a natural stopping point: the search logic was defined, inclusion and exclusion criteria were explicit, and the remaining task was to take those search terms into the world and see how

bob.reed

2 days ago10 min read

Building Meta-Analysis Datasets with AI Assistance: A Case Study. PART 3: Using Sysrev for Title and Abstract Screening and Data Extraction

NOTE : This blog is coauthored with Anne Jayasekara and Weilun (Allen) Wu Introduction This is the third blog in a series on how AI can assist in assembling datasets for meta-analyses. The first blog described how ChatGPT was used to develop a systematic literature search strategy for studies on the relationship between inflation and subjective well-being. The second blog described how that search strategy was executed across four bibliographic databases — Scopus, Business So

bob.reed

2 days ago12 min read

Building Meta-Analysis Datasets with AI Assistance: A Case Study PART 4: Lessons Learned

Introduction This is the fourth and final blog in a series documenting an attempt to use AI tools to assist in constructing a dataset for a meta-analysis on the relationship between inflation and subjective well-being. The three previous blogs described, respectively, how ChatGPT was used to develop a systematic literature search strategy; how that strategy was executed across four bibliographic databases and the resulting records organized in Zotero; and how SysRev's AI-assi

bob.reed

2 days ago9 min read

Another Reason to Prefer Random Effects Over Fixed Effects/UWLS

Introduction Random Effects (RE) versus Fixed Effects (FE) has a long and active debate history. More recently, a “Knapp–Hartung–like” version of FE—Unrestricted Weighted Least Squares (UWLS)—has entered the fray (Stanley & Doucouliagos, 2015 , 2016 ). UWLS is simply conventional weighted least squares using inverse sampling variance weights. It produces identical coefficient estimates to FE, albeit with different standard errors. Among these approaches, RE is by far the most

bob.reed

Jan 213 min read

Stress-Testing Meta-Research with AI Duels

A practical protocol that makes ChatGPT and Gemini challenge each other to surface edge cases, boundary conditions, and hidden assumptions in meta-analysis. Includes a WAIVE vs MAIVE worked example plus GitHub and DOI links.

Tomas Havranek

Dec 12, 20252 min read

MAIVE Is Now on CRAN

We are happy to share that MAIVE (Meta-Analysis Instrumental Variable Estimator) is now available on CRAN : install.packages("MAIVE") MAIVE is a simple tool that helps detect when study results look too precise because of method choices or selective reporting, and it provides an IV-based correction. The method was published recently in Nature Communications . MAIVE is also available in the EasyMeta.org web app, where you can run MAIVE, PET-PEESE, and the EK model with one

Zuzana Irsova

Dec 10, 20251 min read

Highlights from the 2025 MAER-Net Colloquium in Ottawa

by Tom Stanley, Sebastian Gechert, Jerome Geyer-Klingeberg, and Tomas Havranek The Ottawa Colloquium was a wonderful experience and a great success. The quality of presentations and the richness of discussions have never been better. AI featured prominently this year, sparking lively debates that continue on MAER-Net’s blog . We also had many methodological contributions, each offering new ways to understand economics research or to avoid misinterpretation. Of particular no

Tomas Havranek

Oct 31, 20252 min read

Despite Numerous Guidelines, the Gap Remains Wide Between What Meta-Analysts Should Do and What They Actually Do

Introduction The list of guidelines and best-practice recommendations for meta-analysts is extensive. The Cochrane Handbook and a...

bob.reed

Oct 12, 20254 min read

Bias Correction Made Easy: A Web App for Meta-Analysis at EasyMeta.org

EasyMeta.org is a free web app that makes bias correction in meta-analysis simple. Run MAIVE, PET-PEESE, and EK instantly — no coding, no installation.

Zuzana Irsova

Sep 27, 20251 min read

Researchers Can and Should Calculate Power Retrospectively — Just Don’t Use Observed Power

In this blog, I highlight a valid approach for calculating power after estimation—often called retrospective power. I provide a Shiny App...

bob.reed

Sep 4, 20256 min read

🤝 Join the Ecosystem of Reviews for Carbon Pricing – Let’s Build Living Evidence Together! 🤝

Dear colleagues, 🌍 Be part of the Ecosystem of Reviews for Carbon Pricing! This will provide critical evidence on climate solutions to...

s.b.bruns

Aug 29, 20252 min read

AI Tools for Meta-Analysis

AI tools now significantly reduce the workload in meta-analysis, especially for literature search and data collection. ChatGPT’s deep research and Agent functions streamline screening and extraction, while tools like ASReview and NotebookLM offer robust validation. Human oversight remains essential, but fewer co-authors are needed than before. Claude also shows promise in reasoning, though I haven’t tested it systematically yet.

Tomas Havranek

Jul 30, 20254 min read

New Challenges for Meta-Analysis: Attenuation Bias, P-Hacking, Preferred Estimates

Our recent meta-analyses highlight three issues for the field: attenuation bias can rival publication bias in distorting results; new methods like MAIVE address p-hacking more effectively; and author “preferred” estimates may systematically differ from others. Each has implications for best practices in meta-analysis.

Tomas Havranek

Jul 7, 20252 min read

Easy-to-use tool for determining statistical power of published research

(This blog was originally published at the The Replication Network ) Introduction. Your analysis produces a statistically insignificant...

bob.reed

Sep 3, 20245 min read

Addressing sample overlap using Generalized Weights should now be straightforward

Heiko Rachinger and I recently got our paper on addressing sample overlap in economics meta-analyses accepted for publication in the...

pedro.bom

Jun 9, 20242 min read

Univariate PET-PEESE: Why Not Multivariate PET-PEESE?

[NOTE: The R programs that produced the results in this blog are publicly available here: https://osf.io/w2vxg/. “Program1” produced the...

bob.reed

Dec 19, 20237 min read

Methods Guidelines for Meta-Analysis

Zuzana Irsova (Charles University & Anglo-American University in Prague) As discussed at the Palma colloquium, together with Tom, Chris,...

Zuzana Irsova

Nov 27, 20234 min read