statistical-design-audit
CommunityValidate statistical designs for validity before trusting results.
Data & Analytics#statistical audit#statistical design#data validity#p-value analysis#inference validity
Authorstephendor
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill ensures the correctness of statistical designs used in TDL tasks, preventing errors in inference before they reach production.
Core Features & Use Cases
- Audit Dimensions: Checks various aspects like denominator correctness, p-value formula, and estimand validity.
- Audit Dimensions: Includes checks on clustering, null exchangeability, and Markov order.
- Output Format: Provides a clear PASS/CONCERN/FAIL output with actionable insights for improvement.
- Use Case: For a task analyzing a panel dataset with multiple comparisons, the skill will validate the denominators, corrections for multiple comparisons, and the appropriateness of the bootstrap method.
Quick Start
Run the statistical-design-audit skill to validate the statistical design of your task and receive immediate feedback.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 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: statistical-design-audit Download link: https://github.com/stephendor/TDL/archive/main.zip#statistical-design-audit Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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