54 lines
1.3 KiB
Markdown
54 lines
1.3 KiB
Markdown
---
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name: sensitivity-analysis
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description: "Conduct sensitivity analyses to test robustness of findings. Use when: (1) Testing assumption violations, (2) Meta-analysis robustness, (3) Handling missing data, (4) Examining outliers."
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allowed-tools: Read, Write, Bash
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version: 1.0.0
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---
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# Sensitivity Analysis Skill
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## Purpose
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Test whether findings are robust to analytical decisions and assumptions.
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## Types of Sensitivity Analyses
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**1. Exclusion Analyses**
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- Remove outliers
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- Remove high risk-of-bias studies
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- One-study-removed analysis
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**2. Analytical Decisions**
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- Different statistical tests
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- Parametric vs non-parametric
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- Different transformations
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**3. Missing Data**
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- Complete case analysis
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- Best-case scenario
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- Worst-case scenario
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- Multiple imputation
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**4. Measurement**
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- Different outcome definitions
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- Different time points
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- Alternative scoring methods
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## Interpretation
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**Robust Findings:**
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- Results consistent across analyses
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- Conclusions unchanged
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- High confidence
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**Sensitive Findings:**
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- Results vary by decision
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- Interpret with caution
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- Report uncertainty
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## Example
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"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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---
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**Version:** 1.0.0
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