Hi,
I've got a dataset with 7 variables for 8 different species. I'd like
to test the null hypothesis of no difference among species for these
variables. MANOVA seems like the appropriate test, but since I'm
unsure of how well the data fit the assumptions of equal
variance/covariance and multivariate normality, I want to use a
permutation test.
I've been through CRAN looking at packages boot, bootstrap, coin,
permtest, but they all seem to be doing more than I need. Is the
following code an appropriate way to test my hypothesis:
result.vect <- c()
for (i in 1:1000){
wilks <- summary.manova(manova(maxent~sample(max.spec)),
test="Wilks")$stats[1,2]
result.vect <- c(res.vect,wilks)
}
maxent is the data, max.spec is a vector of species names. Comparing
the result.vect with the wilks value for the unpermuted data suggests
there are very significant differences among species -- but did I do
this properly?