sensitivity-analysis

# Sensitivity Analysis Skill

## Purpose
Test whether findings are robust to analytical decisions and assumptions.

## Types of Sensitivity Analyses

**1. Exclusion Analyses**
- Remove outliers
- Remove high risk-of-bias studies
- One-study-removed analysis

**2. Analytical Decisions**
- Different statistical tests
- Parametric vs non-parametric
- Different transformations

**3. Missing Data**
- Complete case analysis
- Best-case scenario
- Worst-case scenario
- Multiple imputation

**4. Measurement**
- Different outcome definitions
- Different time points
- Alternative scoring methods

## Interpretation

**Robust Findings:**
- Results consistent across analyses
- Conclusions unchanged
- High confidence

**Sensitive Findings:**
- Results vary by decision
- Interpret with caution
- Report uncertainty

## Example

"Results were robust to removal of the highest risk-of-bias study (d=0.48 vs d=0.52) and remained significant when using non-parametric tests (p=.002)."

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**Version:** 1.0.0