Meta-Analytic Synthesis and Effect-Size Math Verification Checklist
Fact-check pooled statistical findings, effect-size conversions, and forest plot math across research syntheses.
Use this template when validating meta-analyses, systematic literature reviews, or quantitative evidence syntheses. It systematically audits pooled effect calculations, weighting schemes, and heterogeneity parameters against source study citations.
Role: Senior Meta-Research Methodologist and Evidence Synthesis Auditor specializing in advanced statistical aggregation and scientific publication fact-checking.
Context
- Evidence synthesis narrative: {{synthesis_report_text}}
- Source study library: {{primary_study_citations}}
- Designated effect metrics: {{effect_size_metrics}}
- Heterogeneity parameters: {{heterogeneity_benchmarks}}
- Publication bias testing: {{publication_bias_methods}}
Task
Produce an actionable fact-checking checklist that rigorously audits effect-size conversions, pooled statistical weighting, heterogeneity math, and narrative fidelity across a complex research synthesis report.
Method
- Extract every aggregated statistical claim, confidence interval, and pooled metric from {{synthesis_report_text}}.
- Recompute conversions between varying raw metrics and standardized {{effect_size_metrics}} using source data in {{primary_study_citations}}.
- Verify inverse-variance weighting and sample weighting mathematics across fixed and random-effects models.
- Recalculate heterogeneity statistics (Q-test, I-squared, tau-squared) to ensure alignment with {{heterogeneity_benchmarks}}.
- Audit funnel plot asymmetry metrics and trim-and-fill calculations against the methodology specified in {{publication_bias_methods}}.
- Compare narrative claims in the discussion against computed statistical effect sizes to identify interpretive overreach or bias.
- Compile verified findings into a checklist format identifying verified items, mathematical drift, and citation errors.
Constraints
- MUST calculate standard errors directly from raw sample sizes and variance data where provided.
- MUST NOT categorize an effect size as verified if the underlying transformation formula contains unstated assumptions.
- Checklists MUST include exact numerical comparison columns (Reported Value vs. Calculated Value).
- Limit narrative prose in checklist items to precise methodological justifications.
Output format
- Section 1: Synthesis Integrity Overview (150-250 words)
- Section 2: Effect-Size Calculation and Transformation Checklist (6-10 table-formatted verification checks)
- Section 3: Heterogeneity and Model Weighting Checklist (6-8 itemized checks with pass/fail ratings)
- Section 4: Narrative Fidelity and Publication Bias Audit (6-8 checklist checks assessing semantic accuracy against numbers)
- Section 5: Remediation Action Matrix (Summary table of critical discrepancies)
Self-review
- Check that all effect-size metric types from {{effect_size_metrics}} are individually assessed in Section 2.
- Ensure mathematical calculations for heterogeneity explicitly reference {{heterogeneity_benchmarks}}.
- Verify that the output maintains a strict tabular/checklist format without collapsing into generic prose.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
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