Re: Compare matrices using Chi square for Exploratory
- To: mathgroup at smc.vnet.net
- Subject: [mg114870] Re: Compare matrices using Chi square for Exploratory
- From: Stuart Nettleton <Stuart.Nettleton at uts.edu.au>
- Date: Tue, 21 Dec 2010 00:18:00 -0500 (EST)
- References: <201012200539.AAA22748@smc.vnet.net>
A small addendum to my previous question with the issues that gave rise to
my question about a simple approach to a whole-of-matrix comparison
between original and recreated data.
I tracked down R's chi-squared comparison to Lawley & Maxwell (1962 &
1971). Their Bartlett test suffers from a few disadvantages such as
requiring the inverse of what I have discovered to be an ill-conditioned
matrix or working from correlation matrices rather than original data.
My preference is to use Mathematica's elegant automatic Hypothesis tests
in VarianceEquivalenceTest. At present this function compares vectors of
data, rather than matrices. Mapping across each pair of original and
recreated variables will lead to as many tests results as variables. This
would be quite cumbersome and somewhat analogous to investigating the
percentage of differences between correlation matrices that are greater
than say 0.05, which is interesting but not a test upon which to accept or
reject the number of factors. Thus my question.
Many thanks to those who may be looking at this question.
BTW For those using a Version prior to 8.0, the first line of the package
would need amendment to
BeginPackage["zigzagefa`",{"MultivariateStatistics`"}]
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- References:
- Compare matrices using Chi square for Exploratory Factor Analysis
- From: Stuart Nettleton <Stuart.Nettleton@uts.edu.au>
- Compare matrices using Chi square for Exploratory Factor Analysis