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Construction of Balanced n-ary Designs via Complete Multiset Spaces
Sudesh Srivastav1, Apurv Srivastav2
1Department of Biostatistics and Data Science, Tulane University, New Orleans, USA.
None:
We study balanced n-ary block designs that allow repeated treatments within blocks, motivated by applications in dose-response and repeated-measure experiments. We introduce a master (k + 1)-ary design with explicit replication and pairwise concurrence parameters. Systematic symmetry-preserving deletions generate infinite families of lower-arity balanced designs, for which explicit formulas for replication numbers, structured expressions for pairwise concurrences, and the resulting information matrix under the fixed-effects model are obtained. These results establish a rigorous link between combinatorial Sv -symmetry and statistical optimality. Simulation studies show that the proposed multiset-based designs, by maintaining equireplication, yield lower contrast variances than random multiset arrangements with unequal replication numbers. Potential applications include doseresponse studies, resampling-based simulations, and repeated-measures experiments.
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