Computing Mixed-Design (Split-Plot) ANOVA - The Mathematica Journal
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Computing Mixed-Design (Split-Plot) ANOVA - The Mathematica Journal
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The Mathematica® Journal
Computing Mixed-Design (Split-Plot) ANOVA Sylvain Chartier Denis Cousineau The mixed, within-between subjects ANOVA (also called a splitplot ANOVA) is a statistical test of means commonly used in the behavioral sciences. One approach to computing this analysis is to use a corrected between-subjects ANOVA. A second approach uses the general linear model by partitioning the sum of squares and cross-product matrices. Both approaches are detailed in this article. Finally, a package called MixedDesignANOVA is introduced that runs mixed-design ANOVAs using the second approach and displays summary statistics as well as a mean plot.
‡ Introduction The mixed, within-between subjects design (also called split-plot or randomized blocks factorial) ANOVA is a technique that compares the means obtained by manipulating two factors, one being a repeated-measure factor. Let g be the number of independent groups, each representing one level of the between-subjects factor, let c be the number of measures corresponding to the within-subjects factor, and let ni be the number of subjects in the ith group.
º⋯ y11c º⋯ y12c ª º⋯ y1n1 c º⋯ y21c º⋯ y22c ª º⋯ y2n2 c ª
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ª ª ª ª g ygng 1 ygng 2 º⋯ ygng c First load the package. It is available from www.mathematica-journal.com/data/uploads/2011/10/Chartier.zip. Needs@"MixedDesignANOVA`"D
An example taken from Howell [1] (p. 481) concerns data collected in a study by King [2]. King investigated the effect of midazolam on the motor activity of rats. The rats were measured at six different times (c = 6) and there were g = 3 equal groups of ni = 8 individuals, i = 1 …, g. Hence, the total number of rats measured was N = 24. The data is listed in Table 1.
