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Dear list:

I am having the same problem as Jianbin Fu. In a model with
fixed variances  of latent variables (LVs), the correlations
among the LV's are to be estimated. The variances of the LVs
are fixed to ensure scale identification. The usual alternative,
fixing the relationship between each LV and one of the response
variable, seems to work well in linear factor analysis. However,
with some non-linear response functions, fixing measurement
relations no longer appears to be straightforward.

Would anyone be able to share advice about useful priors for
correlation (not covariance) matrices and how to implement these
in WinBUGS, assuming this is at all possible?

Thank you,

Werner Wothke
Research, Quantitative Methods
CTB/McGraw-Hill
20 Ryan Ranch Road
Monterey, CA 93940
831-393-6472


-----Original Message-----
From: Jianbin Fu [mailto:[log in to unmask]]
Sent: Tuesday, June 24, 2003 9:07 AM
To: [log in to unmask]
Subject: [BUGS] correlation matrix in multivariate normal dist.


Hi folks,

I am trying to use the correlation matrix, instead of covariance matrix, in
the multivariate normal dist. (MVN).  I have tried to first sample the
prior covariance matrix from a Wishart, and then convert it to the
correlation matrix.  But it did not work because in Winbugs 1.4 Wishart can
only be used as the prior distribution of covariance matrix in MVN,
otherwise Winbugs can not find a sampler for Wishart.  The reason that I
want to use correlation matrix is to avoid the scale indeterminacy in
latent trait models.

Any suggestion is highly appreciated on how to model the prior distribution
of correlation matrix in MVN in Winbugs as well as how to solve the scale
indeterminacy in latent trait models when using MCMC.

Jianbin

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