Replication Failure Diagnosis AI Prompt

My replication attempt did not reproduce the original finding. Help me diagnose why and what conclusions to draw.

Original finding: {{original_finding}} (effect size: {{original_es}})
Replication finding: {{replication_finding}} (effect size: {{replication_es}})
Design differences: {{design_differences}}

1. First: quantify the discrepancy
   - Is the replication effect size significantly different from the original? Use a test of heterogeneity (Q statistic or equivalence test)
   - What is the 95% CI of the replication effect size? Does it exclude the original effect size?
   - Could the discrepancy be explained by sampling variation alone? (Both studies may be sampling from the same distribution)

2. Candidate explanations for replication failure:

   a. Statistical explanation (most common for small original studies):
   - The original effect was a false positive (Type I error)
   - The original effect size was inflated by publication bias and the original study was underpowered
   - Both the original and replication are sampling a real effect with high variance
   Evidence for: p-value just below .05 in original; small original N; effect not replicated across multiple attempts

   b. Methodological differences:
   - The replication differed from the original in a consequential way
   - Which specific differences between original and replication could plausibly moderate the effect?
   - A moderator variable was different between studies (population, context, time, operationalization)
   Evidence for: specific, theoretically justified moderator that differed between studies

   c. Context effects:
   - The effect is real but context-dependent
   - The original study was conducted in a specific context that does not generalize
   - Time effects: the phenomenon may have changed since the original study (technology, cultural change)
   Evidence for: original and replication differ in context in a way consistent with a known moderator

   d. Fraud or QRP in the original:
   - The original data were fabricated or p-hacked
   Evidence for: statistical anomalies in the original (GRIM test, SPRITE test, p-curve analysis)

3. What replication failure does and does not tell us:
   - Does NOT tell us: the original finding was definitely wrong, that the original authors did anything improper
   - DOES tell us: the original finding may not be reliable, the effect size is likely smaller than originally reported, the conditions under which the effect occurs need further investigation

4. Recommended next steps:
   - Conduct a mini meta-analysis of all available replications including your own
   - Design a well-powered study explicitly testing the hypothesized moderator
   - Contact the original authors for a collaborative adversarial replication

Return: discrepancy quantification, ranked candidate explanations with supporting evidence, and recommended next steps.