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

  1. #1

    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 (http://www.mathworks.com/matlabcentr...bjectId=12736), 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

  2. #2
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    Did you try R ? http://lib.stat.cmu.edu/R/CRAN/index.html

    It is not that simple, but it is free and it's very powerfull.

    Christophe
    Last edited by Christophe Genolini; 12-10-2007 at 07:56 AM. Reason: don't want the roll a troll

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    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: http://lib.stat.cmu.edu/R/CRAN/index.html). All i found about factor analysis these two:

    http://lib.stat.cmu.edu/R/CRAN/src/c...actoMineR.html
    http://lib.stat.cmu.edu/R/CRAN/src/c...tions/ifa.html

    However none of them have a function to calculate KMO. Any ideas where i could search for more packages? Or any other software?

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    YOu could look for the R mailing list, if you have software for mailing lists the news group is : gmane.comp.lang.R.general

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    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.

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    I know you can join this mailing list through the web and you don't *have* to use a mailing list program.

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    Never tried it but this is a function you should try

    Code: 
    	
    library(corpcor) ###needs the function pcor.sq
    kmo.test <- function(df)
    {
            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 = cor.sumsq/(cor.sumsq+pcor.sumsq)
    	return(kmo)
    }
    > http://tolstoy.newcastle.edu.au/R/help/05/12/17235.html

    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 by mp83; 12-28-2007 at 05:44 PM.

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