Randomized Experimental Design
A randomized experimental design assigns subjects randomly to a treatment group or a Control Group, then compares outcomes. It is the gold standard for establishing causation.
Why randomize?
Random assignment makes the two groups balanced on average across every other variable, known and unknown. Any systematic outcome difference can then be attributed to the treatment.
This is the Method of Difference made statistically rigorous: instead of manually matching cases, you let chance handle it.
Components of a strong RCT
- Random assignment to balance confounders
- Control group receiving no treatment or a placebo
- Blinding (Double-Blind is ideal)
- Pre-registration of the analysis plan, preventing p-hacking
- Adequate sample size
Why RCTs aren't always possible
- Ethics: you cannot randomly assign people to smoke for 40 years
- Practicality: too expensive, too slow, or the population is too small
- External validity: lab conditions may not generalize
When infeasible, observational designs (Prospective, Retrospective) are the fallback at the cost of weaker causal inference.