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OCDs in Group Divisible Design Set-Up

In: Optimal Covariate Designs

Author

Listed:
  • Premadhis Das

    (University of Kalyani, Department of Statistics)

  • Ganesh Dutta

    (Basanti Devi College (Affiliated to University of Calcutta), Department of Statistics)

  • Nripes Kumar Mandal

    (University of Calcutta, Department of Statistics)

  • Bikas Kumar Sinha

    (Indian Statistical Institute)

Abstract

Optimum covariate designs in simple set-ups such as CRD, RBD and some series of BIBD have already been considered. BIBDs do not exist for many parametric combinations. So there is a need to consider other block designs different from the BIBDs suitable for desired parametric combinations. In this chapter, OCDs have been considered for the less-restrictive set-ups of partially balanced incomplete block designs (PBIBD), which are popular among practitioners. As in the case of BIBDs, the OCDs depend much on the methods of construction of the basic PBIBDs. We focus on one well-known subclass of two-associate class PBIBDs, viz. group divisible designs (GDDs) and develop OCDs based on the GDDs. As before, different combinatorial arrangements and tools such as orthogonal arrays, Hadamard matrices and different kinds of matrix-products, viz. Khatri-Rao product, Kronecker product, etc., have been conveniently used to construct OCDs with as many covariates as possible. A list of OCDs based on some classes of GDDs available in Clatworthy, Tables of two-associate class partially balanced designs, (1973) is given in the appendix for ready reference.

Suggested Citation

  • Premadhis Das & Ganesh Dutta & Nripes Kumar Mandal & Bikas Kumar Sinha, 2015. "OCDs in Group Divisible Design Set-Up," Springer Books, in: Optimal Covariate Designs, edition 1, chapter 0, pages 65-88, Springer.
    • Handle: RePEc:spr:sprchp:978-81-322-2461-7_5
    DOI: 10.1007/978-81-322-2461-7_5
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