designing-experiments

Solid

Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.

AI & Automation 2,210 stars 164 forks Updated 1 weeks ago Apache-2.0

Install

View on GitHub

Quality Score: 89/100

Stars 20%
100
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
55
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Designing Experiments Helps select the appropriate causal inference method. ## Decision Framework 1. **Control Group?** * **Yes**: Go to Step 2. * **No**: Consider **Interrupted Time Series (ITS)**. 2. **Unit Structure?** * **Single Treated Unit**: * With multiple controls: **Synthetic Control (SC)**. * No controls: **ITS**. * **Multiple Treated Units**: * With control group: **Difference-in-Differences (DiD)**. 3. **Time Structure?** * **Panel Data** (Multiple units over time): Required for DiD and SC. * **Time Series** (Single unit over time): Required for ITS. ## Method Quick Reference * **Difference-in-Differences (DiD)**: Compares trend changes between treated and control groups. Assumes **Parallel Trends**. * **Interrupted Time Series (ITS)**: Analyzes trend/level change for a single unit after intervention. Assumes **Trend Continuity**. * **Synthetic Control (SC)**: Constructs a synthetic counterfactual from weighted control units. Assumes **Convex Hull** (treated unit within range of controls).

Details

Author
foryourhealth111-pixel
Repository
foryourhealth111-pixel/Vibe-Skills
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
Apache-2.0

Similar Skills

Semantically similar based on skill content — not just same category