I am trying to run non-metric MDS on a dataset that has 28 rows (object = burials) and 27 columns (variables). I have coded it as binomial because my data is both qualitative and quantitative. I am able to get an MDS plot using the code below:
mortdata<-read.csv("Table5.5.csv", header=TRUE)
mortdata
row.names(mortdata) = mortdata[,1]
mortdata
d <- dist(mortdata.alt)
mortdata.fit <- metaMDS(d, k=3)
mortdata.fit
summary(mortdata.fit)
plot(mortdata.fit)
My question is how to identify which variables are causing the variation and add the lines of best fit that correspond to those variables (there should be 3 variables)? Should I be trying to plot in 3D instead?
