Individual skill

designing-experiments

Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.

bundled/skills/designing-experiments/SKILL.md

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# Designing Experiments

Helps choose and specify a research design before data analysis starts. This skill owns study-design decisions: what is treated, what is compared, what outcome is measured, which assumptions are required, which validation or recovery experiment should follow a failed scientific experiment, and which design is defensible.

It does not fit causal models, estimate treatment effects, interpret fitted model output from existing data, or debug software/build failures.

## Decision Framework

1.  **Control Group?**
    *   **Yes**: Go to Step 2.
    *   **No**: Consider **Interrupted Time Series (ITS)**.

2.  **Unit Structure?**
    *   **Single Treated Unit**: