Description Usage Arguments Value Author(s) References Examples
View source: R/summary.Simpson.R
Matrix of all regression results: Each individual cluster and the whole dataset (Alldata) of all clusters, their sample size, and regression estimates (beta and intercept).
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object |
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Not used. |
Returns list called 'Res'. The first object contains clusters numbers, their sample size, and regression estimates (beta and intercept) for variables X and Y defined in the object. The second object is an object of class Mclust, and contains all diagnostics of the cluster analysis. For more details, see package Mclust by Fraley & Raftery.
Rogier Kievit <rogierkievit@gmail.com> & Sacha Epskamp <mail@sachaepskamp.com>
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
Fraley, C., & Raftery, A. E. (1998a) MCLUST: Software for model-based cluster and discriminant analysis. Department of Statistics, University of Washington: Technical Report No.342.
Fraley, C., & Raftery, A. E. (1998b). How many clusters? Which clustering method? - Answers via model-based cluster analysis. Department of Statistics, University of Washington: Technical Report no. 329.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ## Not run:
#Example
#Simulating 100 males
coffeem=rnorm(100,100,15)
neuroticismm=(coffeem*.8)+rnorm(100,15,8)
clusterid=rep(1,100)
males=cbind(coffeem,neuroticismm,clusterid)
#Simulating 100 females
coffeef=rnorm(100,100,15)
neuroticismf=160+((coffeef*-.8)+rnorm(100,15,8))
clusterid=rep(2,100)
females=cbind(coffeef,neuroticismf,clusterid)
data=data.frame(rbind(males,females))
colnames(data) <- c("Coffee","Neuroticism","gender")
example1=Simpsons(Coffee,Neuroticism,clusterid=gender, data=data)
summary(example1)
## End(Not run)
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