Design Experiments and Validate Causal Inference

Designs rigorous experiments and validates causal inference so you lock methodology before examining results. Skills handle power analysis, pre-analysis plans, observational study design, synthetic data generation, and causal audit.

Use /experiment-design for power analysis, pre-analysis plan templates, and QSF parsing, /causal-design to audit identification strategies for observational studies, or /synthetic-data to generate structurally realistic datasets for pilot testing. Use /multi-perspective to stress-test assumptions by exploring a research question from independent viewpoints. Output: validated research designs, power calculations, synthetic datasets, and assumption audits.

Causal-design skill includes method-fitness gates and identification strategy templates. Synthetic-data uses calibration targets and DGP recipes for experimental and observational designs.