Comparison of Re-sampling Methods to Generalized Linear Models and Transformations in Factorial and Fractional Factorial Designs
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May 1, 2012
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Maher Qumsiyeh
University of Dayton
Gerald Shaughnessy
University of Dayton
Abstract
Experimental situations in which observations are not normally distributed frequently occur in practice. A common situation occurs when responses are discrete in nature, for example counts. One way to analyze such experimental data is to use a transformation for the responses; another is to use a link function based on a generalized linear model (GLM) approach. Re-sampling is employed as an alternative method to analyze non-normal, discrete data. Results are compared to those obtained by the previous two methods.
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