Orthogonal Experimental Design

How it works

Risks & contraindications

Highlighted claims

• The L9(3^4) orthogonal design reduces the number of required EA treatment combinations from 81 to 9, while preserving balanced estimation of main effects. — Optimising electroacupuncture parameters for post-stroke hand dysfunction: protocol for a multi-arm randomised controlled trial using orthogonal design
• The orthogonal design evaluates main effects only and is not powered or structured to assess interaction effects between treatment factors. — Optimising electroacupuncture parameters for post-stroke hand dysfunction: protocol for a multi-arm randomised controlled trial using orthogonal design
• Each level of each factor is represented by 33 participants across the nine EA groups because each factor level appears in three groups of 11. — Optimising electroacupuncture parameters for post-stroke hand dysfunction: protocol for a multi-arm randomised controlled trial using orthogonal design
• Factors with p ≤ 0.05 in ANOVA are considered statistically significant; for significant factors with three or more levels, post hoc pairwise comparisons use Bonferroni correction. — Optimising electroacupuncture parameters for post-stroke hand dysfunction: protocol for a multi-arm randomised controlled trial using orthogonal design
• Range analysis using K values and R values determines the relative importance of each factor, with larger R values indicating greater factor influence. — Optimising electroacupuncture parameters for post-stroke hand dysfunction: protocol for a multi-arm randomised controlled trial using orthogonal design