standard error of variances and covariances of the random effects with LME
With lme you could but it would take a while to work it out. There is an approximate Hessian matrix for the parameters that determine the variance-covariance matrix in there somewhere and if you were sufficiently persistent you could convert that apVar component to the scale of the variances and covariances. I believe it is in the scale of the logarithm of the standard deviation and Fisher's z transformation (i.e. the hyperbolic arc tangent) of the correlation.
On 9/29/05, Doran, Harold <HDoran at air.org> wrote:
You cannot. Also, it's not that the distribution of the random effects is not symmetric, but that it *may* not be symmetric, and this is an assumption that should be checked. -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Roel de Jong Sent: Thursday, September 29, 2005 9:20 AM To: r-help at stat.math.ethz.ch Subject: [R] standard error of variances and covariances of the random effects with LME Hello, how do I obtain standard errors of variances and covariances of the random effects with LME comparable to those of for example MlWin? I know you shouldn't use them because the distribution of the estimator isn't symmetric blablabla, but I need a measure of the variance of those estimates for pooling my multiple imputation results. Regards, Roel.
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