Ensuring balance with regard to optimality for known categorical covariates and multiple treatment groups

  • Parantap Nag
  • Pratibha Karki
  • Malabika Boruah
  • Samrat Hore Tripura University

Abstract

Ensuring balanced allocation by achieving optimality for known categorical covariates into two treatment groups has been analytically established with regard to D−, A−, Ds− and As−optimality in Hore et al. (2020) and for E− and Es−optimality has
been discussed by the authors earlier. However, the mathematical complexity of expression of the respective optimality function and mathematical computation increases with more number of treatments. In this work, the relationship between D-optimality and balancing criteria for known categorical covariates across three treatment groups is established through analytical derivation and simulation studies. It has been shown that D−optimality ensures a balanced allocation design, at least as a local optimal solution. Furthermore, simulation studies demonstrate that the balanced allocation design performs uniformly better than random allocation designs.

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List of Potential Reviewers
1. Name :Dr. Sumanta Adhya
Professor
Department of Statistics, WBSU
Email : sumanta.adhya@gmail.com

2. Name : Dr. Atanu Biswas
Professor
ISI, Kolkata
Email : atanu@isical.ac.in

3. Name : Dr. Jagannath Nath
Assistant Professor
Department of FY B Tech,
GH Raisoni College of Engineering and Management, Wagholi, Pune
Corresponding email: jan.21.nath@gmail.com

4. Name : Dr. Akash Singh
Assistant Professor
Department of Mathematics, SRM Institute of Science and Technology (SRMIST), Kattankulathur, Chennai
Email : akashs2@srmist.edu.in
Published
2026-01-19
Section
Special Issue: Global Assembly for Mathematical Modeling and Analysis