[R] incorrect MCMC CIs in pvals.fnc (languageR) ?

[Mike Allerhand]

library(lme4)
library(coda)
library(languageR)

fit = lmer(Reaction~Days + (1|Subject) + (0+Days|Subject), 
data=sleepstudy)

pvals.fnc(fit)$random

# compare with...

samp = mcmcsamp(fit, n=1, trans=FALSE)
HPDinterval(samp)
densityplot(samp, plot=F)

# 'pvals.fnc' reports sigma instead of sigma^2, but it looks like the
# Sbjc.(In) and Sbjc.Days are also sqrt compared with the corresponding
# results from HPDinterval and densityplot. Is that intended?


best wishes,  Mike Allerhand

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[R] sem: standardized covariance estimates

[Mike Allerhand]

Dear all,

How do I get the standardized covariance (the correlation) between two 
latent variables?
'standardized.coefficients' gives standardized path coefficients, but 
not covariances.
The covariance estimates are easily obtained from fit$coeff or 
'summary',  but
EQS reports both the covariance and the correlation, how can I get that?

best wishes,  Mike

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and provide commented, minimal, self-contained, reproducible code.