similar to: SPSS-like factor analysis procedure

Dear colleagues, I've been searching for information on the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (MSA). This statistic is generated in SPSS and is often used to determine if a dataset is "appropriate" for factor analysis -- it's true utility seems quite low, but it seems to come up in stats classes a lot. It did in mine, and a glance through the R-help

Hello, This is in response to a post from a couple of years back regarding Kaiser-Meyer-Olkin Measures of Sampling Adequacy. (http://tolstoy.newcastle.edu.au/R/help/05/12/17233.html) As it turns out, last year Trujillo-Ortiz et al. at the Universidad Autonoma de Baja California wrote and posted a script for MATLAB that does the job. You can see it (with a discussion of KMO statistics) at

I am a beginner when it comes to using R, though fortunately I already know something about statistics. I think factor analysis should be used sparingly, but I occasionally use it. It doesn't seem to me that factanal() provides Kaiser's Measure of Sampling Adequacy, which should be computed for factor problems based on a small number of subjects, though perhaps it is elsewhere. Does anyone

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

I would like to be given sufficient access to http://wiki.centos.org/AdditionalResources/Repositories that I may copy the raw text to a SubPage of my HomePage. I propose to edit the links on that SubPage and submit it for review by anyone who may have sufficient knowledge to validate my changes. I have yet to work with the RPM Package Manager, so I will be making edits that need to be reviewed

hello, I've two questions today. 1) I'm trying to do a scree diagram, I did a Google for a specific command I could used to do so. All I could find is a screeplot. Are they the same command? 2) what command can I used to present a PC scores, eigenvectors of the PC scores, and component correlations? thanks! -- View this message in context:

After doing a PCA using princomp, how do you view how much each component contributes to variance in the dataset. I'm still quite new to the theory of PCA - I have a little idea about eigenvectors and eigenvalues (these determine the variance explained?). Are the eigenvalues related to loadings in R? Thanks, Paul -- View this message in context:

Hello! Very often one can hear that MDS usually ends with two-dimensional solution. Of course, there are methods, like Scree-test (proposed by Kruskal and Wish, 1981), to determine optimal number of dimensions. However, I am trying to find references to this two-dimensional gold-standard. Can anyone point me to authors which explicitly states that two-dimensions are typical and easiest to

Hello, I am having some problems with fitting an ARMA model to my time series data (randomly generated numbers). The thing is I have tried many packages [tseries, fseries, FitARMA etc.] and all of them giving very different results. I would appreciate if someone could post here what the best package is for my purpose. Also, after having done the fitting, I would like to check for the model's

Hi! I am an R beginer, so perhaps this is a quite simple question... After using the lmer command (under the lme4 package) for fitting a mixed model, it was impossible to use de command plot(model) for checking model adequacy. R returns this message: "Error in as.double(y) : cannot type '%s' coerce to vector". Could anyone be so kind to tell me what to do? How can I

My previous post about prcomp and princomp was done in some haste as I had long ago indicated to Kurt that I would try to have this ready for the June release, and it appeared that I would miss yet another release. I also need to get it out before it becomes hopelessly buried by other work. Brian Ripley kindly pointed out some errors, and also pointed out that I was suggesting replacing some

Excellent. Thank you; a most useful option of the MoinMoin wiki. On Tue, Dec 9, 2014 at 1:26 PM, Alan Bartlett <ajb at elrepo.org> wrote: > On 9 December 2014 at 21:19, PatrickD Garvey <patrickdgarveyt at gmail.com> > wrote: > > I would like to be given sufficient access to > > http://wiki.centos.org/AdditionalResources/Repositories that I may copy > the >

Hi! Is there an easy way to add to the scree-plot labels to each value pertaining to the cumulative proportion of explained variance? Thanks and a happy new year Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com --------------------------------------------------- M-TD Modelling and Technology Development PSE-C

Hi, If I use the eigen() function to find the eigenvalues of a matrix, how can I find the eigenvector corresponding to the largest eigen value? Thanks! [[alternative HTML version deleted]]

Dear all, the dataset documented under ?crimtab was also used in: @article{TreloarAE1934, title = {The adequacy of "{S}tudent's" criterion of deviations in small sample means}, author = {Treloar, A.E. and Wilder, M.A.}, journal = {The Annals of Mathematical Statistics}, volume = {5}, pages = {324-341}, year = {1934} } The following is

Hello, I am using function princomp from the package psych. I have my principle component object mypc: mypc <- princomp(covmat=mycor) plot(mypc) # shows me a screeplot Question: how could I actually see the values displayed in the screeplot. I don't mean on the graph - I just want to know the actual value for each component (e.g., 10, 3.2, 1.8, etc.) I need to know how much variance,

This is a more general statiscal question, not specific to R: As I move through my masters curriculum in statistics, I am becoming more and more attuned to issues of model fit and diagnostics (graphical methods, AIC, BIC, deviance, etc.) As my regression professor always likes to say, only draw substantive conclusions from valid models. Yet in published articles in my field (medicine), I

Hello Everyone,   I’m a SAS user who has recently become interested in sequential clinical trials designs. I’ve discovered that the SAS based approaches for these designs are either too costly or are “experimental.” So now I’m looking for alternative software. Two programs that seem promising are SPLUS Seqtrial and R.   I recently obtained a 30 day trial for the SPLUS Seqtrial add-on and have

I am trying to check the results from an Eigen decomposition and I need to force a scalar multiplication. The fundamental equation is: Ax = lx. Where 'l' is the eigen value and x is the eigen vector corresponding to the eigenvalue. 'R' returns the eigenvalues as a vector (e <- eigen(A); e$values). So in order to 'check' the result I would multiply the eigenvalues

Hi, I am using R to do a principal components analysis for a class which is generally using SPSS - so some of my question relates to SPSS output (and this might not be the right place). I have scoured the mailing list and the web but can't get a feel for this. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component