Abstract
This article develops formulas for panel size for designed experiments. Using a simple three-attribute problem, the author discusses situations for determining panel sizes in the context of the multiple regression and logistic regression formulations. Modeling member net present value and response rate as functions of the attributes of an acquisition program are the two situations considered. The article also has a pedagogical flavor and discusses how the maximum likelihood approach is used in estimating the variance of the partial logistic regression coefficients. Illustrative examples are provided to show the application of the formulas. For marketers, the bottom line result is useful: testing with designed experiments requires far fewer observations than classical tests of hypotheses, where pairwise comparisons are carried out. This is because all the information is used simultaneously to estimate model coefficients. For a non-technical overview, see the end of the article.
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