Simpsons (version 0.1.0)

cluster: Extract clustered subsets

Description

After running a Simpsons, the function 'cluster' extracts desired clusters from "Simpsons" object.

Usage

cluster(x, clusters)

Arguments

x

Object of class Simpson

clusters

Define which clusters should be returned. Can range from 1 to maximum number of clusters detected in the Simpsons analysis.

Value

Returns list

Details

Returns list

References

Kievit, R.A., Frankenhuis, W. E. , Waldorp, L. J. & Borsboom, D. (in preparation). Simpson's Paradox in Psychological Science: A Practical Guide. http://rogierkievit.com/simpsonsparadox.html

Examples

## Not run: 
# #example 2. Here we estimate the relationship between 'Coffee' and #'Neuroticism'. 
# #As opposed to example 1, we have not measured any possible clustering #identifiers 
# #such as gender, so we want to estimate whether there is evidence for #clustering based 
# #only on the data we measured: Coffee and Neuroticism.
# 
# #generating data 
# Coffee1=rnorm(100,100,15)
# Neuroticism1=(Coffee1*.8)+rnorm(100,15,8)
# g1=cbind(Coffee1, Neuroticism1)
# Coffee2=rnorm(100,170,15)
# Neuroticism2=(300-(Coffee2*.8)+rnorm(100,15,8))
# g2=cbind(Coffee2, Neuroticism2)
# Coffee3=rnorm(100,140,15)
# Neuroticism3=(200-(Coffee3*.8)+rnorm(100,15,8))
# g3=cbind(Coffee3, Neuroticism3)
# data2=data.frame(rbind(g1,g2,g3))
# colnames(data2) <- c("Coffee","Neuroticism")
# 
# example2=Simpsons(Coffee,Neuroticism,data=data2) 
# cluster(example2,2) #extracts data belonging to cluster 2
# cluster(example2,c(1,3) #extracts all datapoints belonging to clusters 1 and 3
# ## End(Not run)