ds-receiving-analysis-review

To verify analysis review feedback, rephrase each comment in precise analytical terms and check it against the notebook, SQL, and experiment design artifacts. Separate methodological claims affecting denominators or inference from presentation preferences before implementing any changes.

Handling reviewer comments that weaken causal inference requires pushing back on suggestions that introduce leakage, post-treatment metrics, or ignore randomization units. Evaluate feedback for methodological validity against the actual experiment design before applying any modifications.

Separating methodological corrections from style preferences involves distinguishing claims that affect design, implementation, denominators, and units from comments that only impact presentation or readability. This prevents applying non-methodological preferences that alter statistical conclusions.

When peer review feedback is unclear or ambiguous, use a fail-closed approach to stop and ask for clarification. Avoiding partial updates on blocking items prevents changes that could alter the interpretation of your statistical conclusions.

You should rerun affected sections immediately after fixing blocking methodological issues in a notebook. Follow a controlled implementation order: clarify ambiguous items first, fix methodological issues next, then address reproducibility, rerunning after each fix.

Yes, the analysis review process works for exploratory and primary statistical results by maintaining causal clarity guardrails. It prevents reviewer suggestions from blurring the distinction between exploratory findings and primary conclusions during the feedback implementation.