Experimental design study demonstrates orthogonal balanced designs for mixture order-of-addition experiments, suggesting efficient factor screening with fewer experimental runs.
In order to enable factor screening in large‐scale mixture‐order‐of‐addition (MOofA) experiments, this paper develops a new methodology. Based on the theory of complete pairwise partitioning, we decompose the full MOofA model into several sub‐models and construct an orthogonal balanced design for these sub‐models. The orthogonal balanced design ensures both mutual orthogonality among order terms within each sub‐model and elimination of confounding between order terms and mixture main effects. This approach effectively reduces the number of experimental runs while enabling efficient and accurate identification of significant factors.
No takes yet. Share an insight, caveat, or question.
Li et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: