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Designs to Minimize Loss of Information in Polynomial Regression

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  • G. V. Dyke

Abstract

In reporting an experiment that includes a factor applied at many levels one may be willing to neglect certain terms of an assumed polynomial response curve. E.g. if there are 7 levels one may assume a cubic curve and neglect the quartic, quintic and sextic terms. If the block size is less than a replicate a “best” confounding can be selected by use of a standard computer program. “Best” here means “with minimum loss of information on (say) linear, quadratic and cubic terms”. The analysis of such an experiment involves covariance on a few simple dummy variates. The procedure for design and analysis for 7 or 8 levels in blocks of 4 is given in detail and the method of extension to other cases is indicated. The paper is presented as a modest example of the possible use of electronic computers to scan many possible designs and to indicate which of them are best using simple criteria, but without making exact orthogonality a sine qua non.

Suggested Citation

  • G. V. Dyke, 1974. "Designs to Minimize Loss of Information in Polynomial Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(3), pages 295-299, November.
    • Handle: RePEc:bla:jorssc:v:23:y:1974:i:3:p:295-299
    DOI: 10.2307/2347122
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