Peer Review Statistics Critique AI Prompt

Critically evaluate the statistical methods and reporting in this paper I am reviewing.

Paper abstract/methods/results: {{paper_content}}

Systematically check for the following statistical issues:

1. Study design and causal inference:
   - Does the study design support the causal claims made in the discussion?
   - Are observational data used to support causal conclusions without adequate justification?
   - Is confounding adequately addressed?

2. Sample size and power:
   - Was a power analysis reported? Does the achieved sample size match the power analysis?
   - Is the study adequately powered for the primary outcome? (Effect size and sample size allow calculation)
   - Is the study appropriately cautious about null results given potential underpowering?

3. Multiple comparisons:
   - How many outcomes were tested? Were corrections for multiple comparisons applied?
   - Are results from exploratory analyses clearly labeled as such?
   - Is there evidence of outcome switching (primary outcome appears to have been changed post-hoc)?

4. Effect sizes and practical significance:
   - Are effect sizes reported for all main findings?
   - Are confidence intervals reported?
   - Is the distinction between statistical significance and practical significance made?

5. Specific red flags:
   - p-hacking indicators: p-values clustered just below 0.05, unusual number of 'marginally significant' results (p = .06, .07, .08)
   - HARKing (Hypothesizing After Results are Known): post-hoc hypotheses presented as a priori
   - Selective reporting: were all pre-specified outcomes reported? Are non-significant results reported?
   - Base rate neglect: does the probability of a true finding justify the strength of the conclusion?
   - Overfitting: in predictive models, is there a held-out test set? Is in-sample fit used to claim out-of-sample performance?

6. For each issue identified:
   - Severity: does this issue invalidate the conclusions, weaken them, or require clarification?
   - Recommended author action: specific request for analysis, reporting, or language change
   - Reviewer language: suggest wording appropriate for a peer review

Return: structured peer review critique organized by issue, severity ratings, and specific revision requests.