sensitivity-analyst
CommunityCausal inferences with robust sensitivity checks
Data & Analytics#robustness#causal-inference#sensitivity-analysis#mediation#unmeasured-confounding#E-values
AuthorData-Wise
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a structured framework for conducting sensitivity analyses in causal inference, enabling researchers to evaluate robustness against unmeasured confounding, measurement error, and model misspecification.
Core Features & Use Cases
- E-values computation for various effect measures (RR/HR)
- Rosenbaum bounds for assessing hidden bias in matched studies
- Mediation sensitivity analysis to assess natural indirect effects
- Tipping point analysis and contour visualizations to identify robustness thresholds
- Reusable R functions for grid searches, interpretation, and plotting
Quick Start
To begin, load the sensitivity analysis functions and run a quick check:
- sensitivity_unmeasured(estimate = 0.6, se = 0.15)
- compute_evalue(estimate = 0.6, lo = 0.4, hi = 0.8, type = "RR")
- plot_tipping_point(estimate = 0.6, se = 0.15)
Dependency Matrix
Required Modules
ggplot2
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: sensitivity-analyst Download link: https://github.com/Data-Wise/scholar/archive/main.zip#sensitivity-analyst Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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