Hi All,
How do i calculate KMO for a dataset?
*Dataset:---------------------*
m1 m2 m3 m4 m5 m6 m7 m8
1 2 20 20 2 1 4 14 12
2 9 16 3 5 2 5 5 15
3 18 18 18 13 17 9 2 4
4 7 7 2 12 2 11 11 11
5 7 8 5 19 5 2 20 18
6 7 4 7 4 7 9 3 3
7 5 5 5 12 5 13 13 12
8 6 6 4 3 5 17 17 16
9 12 12 4 2 4 4 14 14
10 5 14 6 19 6 2 20 20
11 13 13 13 20 10 10 10 9
12 3 3 3 11 6 15 15 12
13 2 2 2 7 5 5 6 16
14 11 11 10 4 10 10 10 10
15 1 1 1 8 4 16 16 17
16 23 23 3 4 3 3 3 3
17 4 4 6 9 8 17 8 18
18 8 8 5 9 7 7 7 9
19 6 7 8 3 8 4 4 7
20 8 11 9 3 2 2 2 3
**
*SPSS results for the above dataset:--------*
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.(KMO)
0.350911931549742
*Got a R-function:-----* (
http://www.opensubscriber.com/message/r-h...@stat.math.ethz.ch/2776549.html)
kmo.test <- function(df){
###
## Calculate the Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
## Input should be a data frame or matrix, output is the KMO statistic.
## Formula derived from Hutcheson et al, 1999,
## "The multivariate social scientist," page 224, ISBN 0761952012
## see
<http://www2.chass.ncsu.edu/garson/pa765/hutcheson.htm><http://www2.chass.ncsu.edu/garson/pa765/hutcheson.htm%3E>
###
cor.sq = cor(df)^2
cor.sumsq = (sum(cor.sq)-dim(cor.sq)[1])/2
library(corpcor)
pcor.sq = cor2pcor(cor(df))^2
pcor.sumsq = (sum(pcor.sq)-dim(pcor.sq)[1])/2
kmo = sus.cor.ss/(sus.cor.ss+sus.pcor.ss)
return(kmo)
}
What is this object "*sus.cor.ss*"?I get errors
> sus.cor.ss
Error: object "sus.cor.ss" not found
Thanks in advance
Moumita
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