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Choice of Confounding in the 2 k Factorial Design in 2 b Blocks

Author

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  • Francis C. Eze

    (Department of Statistics, Nnamdi-Azikiwe University, Awka, Anambra State, Nigeria)

Abstract

In 2k complete factorial experiment, the experiment must be carried out in a completely randomized design. When the numbers of factors increase, the number of treatment combinations increase and it is not possible to accommodate all these treatment combinations in one homogeneous block. In this case, confounding in more than one incomplete block becomes necessary. In this paper, we considered the choice of confounding when k > 2. Our findings show that the choice of confounding depends on the number of factors, the number of blocks and their sizes. When two more interactions are to be confounded, their product module 2 should be considered and thereafter, a linear combination equation should be used in allocating the treatment effects in the principal block. Other contents in other blocks are generated by multiplication module 2 of the effects not in the principal block. Partial confounding is recommended for the interactions that cannot be confounded.

Suggested Citation

  • Francis C. Eze, 2019. "Choice of Confounding in the 2 k Factorial Design in 2 b Blocks," Academic Journal of Applied Mathematical Sciences, Academic Research Publishing Group, vol. 5(5), pages 50-56, 05-2019.
    • Handle: RePEc:arp:ajoams:2019:p:50-56
    DOI: 10.32861/ajams.55.50.56
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