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designing-experiments

@pymc-labs/CausalPy
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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.

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SKILL.md

name designing-experiments
description 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.

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).