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.
Conducts sensitivity analyses to test robustness of findings. Triggers when testing assumption violations, handling missing data, examining outliers, or validating meta-analysis results.
/plugin marketplace add astoreyai/ai_scientist/plugin install research-assistant@research-assistant-marketplaceThis skill is limited to using the following tools:
Test whether findings are robust to analytical decisions and assumptions.
1. Exclusion Analyses
2. Analytical Decisions
3. Missing Data
4. Measurement
Robust Findings:
Sensitive Findings:
"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)."
Version: 1.0.0