I have a data frame containing a half dozen continuous measurements and over a dozen ordinal variables (such as, death, fever, symptoms etc). I would like to run a box matrix test and I am using biotools' boxM, but it allows to run only one ordinal group at the time. For instance: ``` >data(iris) >boxM(iris[,1:4], iris[,5])
Box's M-test for Homogeneity of Covariance Matrices data: iris[, 1:4] Chi-Sq (approx.) = 140.94, df = 20, p-value < 2.2e-16 >bins <- c(1,2); iris$bin <- findInterval(iris$Petal.Width, bins) >iris$bin = factor(iris$bin) >boxM(iris[,1:4], iris[,6]) Box's M-test for Homogeneity of Covariance Matrices data: iris[, 1:4] Chi-Sq (approx.) = 140.94, df = 20, p-value < 2.2e-16 >boxM(iris[,1:4], iris[,5:6]) Error in boxM(iris[, 1:4], iris[, 5:6]) : incompatible dimensions! ``` Is there a way to check for equality of variance-covariance on multiple groups simultaneously? Thanks ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
