AI for Detecting Publication Bias in Meta-Analyses

Publication bias detection extends beyond traditional methods with AI assistance; comprehensive detection improves meta-analysis validity.

What AI does well here

• Apply traditional methods (funnel plots, Egger test) plus AI-assisted analysis
• Use p-curve analysis to detect questionable research practices
• Surface unpublished studies through grey literature search
• Document detection methodology and findings in meta-analysis publications

What AI cannot do

• Eliminate publication bias entirely
• Substitute statistical detection for substantive evaluation
• Find studies that simply don't exist publicly

Practice this safely

Use a real but low-risk workflow from your day. Treat AI as a drafting and organizing layer, then verify the output before anyone relies on it.

1. 1Ask AI to explain publication bias in plain language, then underline anything that sounds uncertain or too broad.
2. 2Give it one detail from "AI for Detecting Publication Bias in Meta-Analyses" and ask for two possible next steps plus one reason each step might be wrong.
3. 3Check meta-analysis against a trusted source, teacher, adult, expert, or original document before you use it.