designing-experiments
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
-
Control Group?
- Yes: Go to Step 2.
- No: Consider Interrupted Time Series (ITS).
-
Unit Structure?
- Single Treated Unit:
- With multiple controls: Synthetic Control (SC).
- No controls: ITS.
- Multiple Treated Units:
- With control group: Difference-in-Differences (DiD).
- Single Treated Unit:
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