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tooluniverse-epidemiological-analysis
End-to-end observational epidemiology analysis — from research question (PECO Population/Exposure/Comparator/Outcome) to publication-ready statistical report. Covers cohort/case-control/cross-sectional design, regression with confounders, propensity scoring, sensitivity analysis. Writes Python code for every step. Use for epidemiology study analysis, NHANES/UK-Biobank-style analyses.
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# Epidemiological Data Analysis
Complete workflow for observational epidemiology — from research question to publication-ready report. Write and run Python code for every step. Never describe what you "would do" — do it.
## Step 1: Formulate the Research Question (PECO Framework)
Define **P**opulation, **E**xposure, **C**omparator, **O**utcome before touching data.
- **Population**: Who? (e.g., adults aged 20-79, cancer patients stage III+, ICU admissions)
- **Exposure**: What factor? (e.g., nutrient intake, drug treatment, gene mutation, environmental pollutant)
- **Comparator**: Vs. what? (e.g., lowest tertile, unexposed, wild-type, placebo)
- **Outcome**: What health event? (e.g., disease incidence, survival time, biomarker level, mortality)
**Study design check**: Does the question require temporality?