March 2019
Beginner to intermediate
448 pages
13h 14m
English
Content preview from R Statistics Cookbook
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As it happens with the univariate case, we should also check whether the covariance matrices are the same between the two samples. This obviously requires a more sophisticated test (compared to the univariate test), because we are now working with matrices. There are several possible strategies, although a simple one is to use Box's M test, which can be obtained via the heplots package.
We need to create a combined dataset and a grouping variable to use boxM:
library(heplots) class1$group = "1" class2$group = "2" combined = rbind(class1,class2) combined$group = as.factor(combined$group) boxM(cbind(combined$Math,combined$History,combined$Sociology)~group,data = combined)
The preceding code generate the following output for ...
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