var-covar matrices comparison
David Duffy <David.Duffy at qimr.edu.au> writes:
Date: Mon, 20 Feb 2006 16:43:55 -0600 From: Aldi Kraja <aldi at wustl.edu> Hi, Using package gclus in R, I have created some graphs that show the trends within subgroups of data and correlations among 9 variables (v1-v9). Being interested for more details on these data I have produced also the var-covar matrices. Question: From a pair of two subsets of data (with 9 variables each, I have two var-covar matrices for each subgroup, that differ for a treatment on one group (treatment A) vs (non-Treatment A). Is there a software that can compare if two var-covar matrices are statistically the same?
This can be done in various structural equation modelling packages. I don't think it can be done automatically using the sem package, as that does not allow multiple groups. You can roll your own LR test (assuming MVN): f <- (N-1) * (log(det(E)) - log(det(O)) + sum(diag((O %*% solve(E))))-p) N=size of group p=number of variables E=expected covariance matrix O=observed covariance matrix
..and an asymptotic approximation to order n^-3 is found in TW Anderson: An Introduction to Multivariate Statistical Analysis (formula (7) section 10.5 in my 1958, 1st ed. reprint).
where in your example, E will be the observed covariance matrix for the pooled groups. There are GLS etc alternatives - see eg Bollen's book on SEM. | David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
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