Morpho (version 1.0-1)

permudist: performs permutation testing for group differences.

Description

This function compares the distance between two groupmeans to the distances obtained by random assignment of observations to this groups.

Usage

permudist(data, groups, rounds = 1000, which = 1:2, mc.cores = detectCores())

Arguments

data

array or matrix containing data

groups

factors determining grouping.

rounds

number of permutations

which

in case the factor levels are >2 this determins which factorlevels to use

mc.cores

integer: determines how many cores to use for the computation. The default is autodetect. But in case, it doesn't work as expected cores can be set manually. Parallel processing is disabled on Windows due to occasional errors.

Value

• permudist
  vector containing distances between random group means.
• dist
  distance between actual group means
• p.value
  p-value obtained by comparing the actual distance to randomly acquired distances.

Examples

data(boneData)
proc <- procSym(boneLM)
groups <- name2factor(boneLM,which=3)
perm <- permudist(proc$PCscores[,1:10], groups=groups, mc.cores=2, rounds=100)
#visualize results
hist(perm$permudist, xlim=c(0,0.1),main="measured vs. random distances",
     xlab="distances")#random distances
points(perm$dist,50,col=2,pch=19)#actual distance
text(perm$dist,70,label=paste("actual distance\n(p=",perm$p.value,")"))

## now we concentrate only on sex dimorphism between Europeans
groups <- name2factor(boneLM,which=3:4)
levels(groups)
perm1 <- permudist(proc$PCscores, groups=groups,which=3:4, mc.cores=2, rounds=100)
# plot histogram of random distances
hist(perm1$permudist, xlim=c(0,0.1),main="measured vs. random distances",
     xlab="distances")
points(perm1$dist,50,col=2,pch=19)#actual distance
text(perm1$dist,60,label=paste("actual
distance\n(p=",perm1$p.value,")"))