Influential observation review ============================== StatMedAnalysis | Original downloadable worksheet | 6 November 2026 Distinguish data errors, unusual observations and model influence. How to use this worksheet Identify observations flagged by appropriate leverage or influence diagnostics in the approved environment. Check source accuracy without placing identifiers here. Compare model results with and without flagged observations as a sensitivity exercise, not an automatic deletion rule. Explain why any exclusion is scientifically justified. Save a working copy and keep the original blank version. Use public, hypothetical or aggregate information only; do not enter patient identifiers, credentials or confidential records. Keep source evidence in your approved project workspace. Mark unresolved text fields UNKNOWN or NOT REPORTED with a reason; never substitute zero for an unknown count. Project/version __________________ Prepared by role/date __________________ Working fields 1. Model and diagnostic definition Response/evidence: _________________________________________________________ ___________________________________________________________________________ 2. Aggregate flagged count Response/evidence: _________________________________________________________ ___________________________________________________________________________ 3. Source-data verification outcome Response/evidence: _________________________________________________________ ___________________________________________________________________________ 4. Leverage versus residual concern Response/evidence: _________________________________________________________ ___________________________________________________________________________ 5. Scientific reason observation is plausible Response/evidence: _________________________________________________________ ___________________________________________________________________________ 6. Sensitivity effect on estimates Response/evidence: _________________________________________________________ ___________________________________________________________________________ 7. Exclusion decision and timing Response/evidence: _________________________________________________________ ___________________________________________________________________________ 8. Retained audit trail Response/evidence: _________________________________________________________ ___________________________________________________________________________ Hypothetical worked case A fictional observation has high leverage because its predictor value is unusual but correctly recorded. Removing it solely because the coefficient changes would hide model sensitivity rather than resolve an error. Decision rule and limitations Correct documented errors and justify exclusions independently of preferred results. Report material sensitivity when valid observations strongly affect conclusions. Decision _______________________ Remaining uncertainty ____________________ Next action ____________________ Owner / review date ______________________ Independent check and discrepancy resolution _______________________________ Official method or reporting reference checked 6 November 2026 https://www.statsmodels.org/stable/diagnostic.html This is an original planning aid, not an official checklist, validated instrument, clinical recommendation or certificate of expert approval. Apply the referenced guidance to the specific design and record any additional requirements.