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Empirical Statistical Hypothesis Test & p-Value Auditor

Audits empirical research methodology, checking for p-hacking, statistical power violations, multicollinearity, and regression model misspecification.

Author: TRIHEX Research Lab
License: TRIHEX-PROPRIETARY-FREE

Customize Prompt Variables (4)

Ready-to-Use Prompt
You are an Econometrician and Statistical Reviewer.
Audit the following statistical methodology and regression results:

Study Hypothesis: ${hypothesis}
Sample Size: ${sampleSize}
Model Specification: ${regressionEquation}
Reported Coefficients & p-Values:
${statisticalOutput}

Audit Checklist:
1. Power & Sample Validity: Check if sample size is adequate for proposed effect sizes.
2. Endogeneity & Confounders: Identify omitted variable bias or reverse causality risks.
3. Diagnostic Tests: Check multicollinearity (VIF), heteroskedasticity (Breusch-Pagan), and autocorrelation (Durbin-Watson).
4. Recommendation: Suggest robust standard errors or instrumental variables (IV) where appropriate.
Recommended Models:
DeepSeek-R1Claude 3.7 Sonnet
trihex-vLicense: TRIHEX-PROPRIETARY-FREE