Generate crossover study designs with proper sequence allocation and calculate sample sizes accounting for within-subject correlation. Supports Williams Latin Square and balanced designs with optional washout period planning.
Balanced for carryover effects — each treatment follows every other treatment equally
Get properly formatted citations for academic work. Citing the tools you use keeps your methods reproducible and reviewable.
StatsCalculators Team. (2026). Crossover Design Calculator. StatsCalculators. Retrieved September 17, 2026 from https://statscalculators.com/calculators/experimental-design/crossover-design-calculator
A crossover design is an experimental setup where each subject receives more than one treatment in sequence, separated by washout periods. Because each subject serves as their own control, between-subject variability is removed from the error term, dramatically increasing statistical power.
Each treatment follows every other treatment exactly once, controlling for first-order carryover effects.
All possible treatment sequences are included, providing complete balance across all orderings.
A washout period is a gap between treatment periods that allows the effect of the previous treatment to dissipate before the next treatment begins. Inadequate washout leads to carryover effects — where treatment A influences the observed response to treatment B.
The efficiency gain of a crossover design over a parallel design depends on the within-subject correlation (ρ) — how correlated repeated measurements on the same subject are. Higher correlation means greater efficiency.
Typical within-subject correlations range from 0.3–0.7 for most clinical and behavioral outcomes.
