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st: Estimation metric of variance components in gllamm


From   Sascha Peter <sascha.peter@uni-hamburg.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: Estimation metric of variance components in gllamm
Date   Sat, 23 Jun 2012 10:41:18 +0200

Dear Stata-Users,
I have a question regarding the estimation metric of random effects covariances in gllamm. I want to use estimation results from Stata's xtmepoisson as starting values to estimate a multilevel Poisson regression in gllamm. Since the estimation metric for the variance components of the two programs differ, variances and covariances stored in e(b) after xtmepoisson have to be transformed before these can be used as starting values for gllamm. xtmepoisson uses the log of the standard deviation as estimation metric and gllamm uses the standard deviation. So exponentiation of the respective elements in e(b) will do the job. xtmepoisson uses the arc-hyperbolic tangents of correlations to estimate covariance components. However,I was not able to figure out in which metric these are estimated in gllamm. Which transformation has to be applied to the covariance components in e(b) so that these estimates can be used as starting values in gllamm?

Thank you very much,
Sascha

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