Need a simple, free software to calculate the Kaiser-Meyer-Olkin measure

Greetings :)

I have an urgent need for a easy to use, free software to calculate the Kaiser-Meyer-Olkin (KMO) measure of matrices with ~1700 observations. I have tried to use Trujillo's m-file (, but its not working.

Also, in case someone mentions Bartlett's Sphericity Test, the data i work on cannot be normalized, and as far as i know, Bartlett can only be applied to normalized data.

Thanks in advance :D
I have installed R and managed to access my data files through it. However, it seems i have to download a package that contains the KMO test. The list of available packages is quite large (looking here: All i found about factor analysis these two:

However none of them have a function to calculate KMO. Any ideas where i could search for more packages? Or any other software?
Trying to configure thunderbird to work on gmane.comp.lang.R.general, and trying to use my yahoo mail with that. Does that work or do i need a pop3 email? Is there any other config on gmane.comp.lang.R.general that i need to connect to it?

Solving this is tougher than i thought :( Im considering breaking into the statistics lab at uni at night with a pendrive.


TS Contributor
Never tried it but this is a function you should try

library(corpcor) ###needs the function [B]pcor.sq[/B]
kmo.test <- function(df)
        cor.sq = cor(df)^2
	cor.sumsq = (sum(cor.sq)-dim(cor.sq)[1])/2
	pcor.sq = cor2pcor(cor(df))^2
	pcor.sumsq = (sum(pcor.sq)-dim(pcor.sq)[1])/2
	kmo = cor.sumsq/(cor.sumsq+pcor.sumsq)

You can use (never used it either...)

Factor -- a comprehensive factor analysis program. Provides univariate and multivariate descriptive statistics of input variables (mean, variance, skewness, kurtosis), Var charts for ordinal variables, dispersion matrices (user defined , covariance, pearson correlation, polychoric correlation matrix with optional Ridge estimates). Uses MAP, PA (Parallel Analysis), and PA - MBS (with marginally bootstrapped samples) to determine the number of factors/components to be retained. Performs the following factor and component analyses: PCA, ULS (with Heywood correction), EML, MRFA, Schmid-Leiman second-order solution, and Factor scores. Rotation methods: Quartimax, ,Varimax , Weighted Varimax, Orthomin , Direct Oblimin, Weighted Oblimin, Promax, Promaj , Promin, and Simplimax. Indices used in the analysis: dispersion matrix tests (determinant, Bartlett's, Kaiser-Meyer-Olkin), goodness of fit: Chi-Square ,non-normed fit index, comparative fit index, goodness of fit index, adjusted GFI, RMS error of approx, and estimated non-centrality parameter (NCP), reliabilities of rotated components , simplicity indices: Bentler’s, and loading simplicity index. Provides mean, variance and histogram of fitted and standardized residuals, and automatic detection of large standardized residuals.
Last edited: