Random effects in summary lme

["Jimenez-Leal William" <william.jimenezleal@lsc.gov.uk>]

 

Dear S plus users,

 

I am fitting a bunch of mixed effects logistic regressions using glmmPQL and I have a little problem extracting their random coefficients. I am modeling the probability of passing an exam against student's prior attainment, allowing the latter to vary randomly across schools. Looks something like this

 

a<-glmmPQL(POINTS~PA +PA2+PA3,random=~PA|INST, family=binomial(link=logit), data="" niter=1000)

 

('pa' is the prior attainment, 'inst' is school)

 

Normally, I just produce a summary of this object, which gives you the corresponding standard deviations and correlations, and work out the variance-covariance matrix from there. This is the summary:

 

summary(a)

Linear mixed-effects model fit by maximum likelihood

 Data: k

       AIC      BIC    logLik

  18142.24 18189.96 -9063.118

 

Random effects:

 Formula:  ~ PA | INST

 Structure: General positive-definite

                StdDev   Corr

(Intercept) 3.68174225 (Intr)

    PA      0.09902275 0.253

   Residual 0.60168538      

 

Variance function:

 Structure: fixed weights

 Formula:  ~ invwt

 

(Etc, etc)

Number of Observations: 2881

Number of Groups: 142

 

 

The problem is that when I extract this matrix from the summary object directly, the random effects numbers do not match.

 

summary(a)$modelStruct$reStruct

 

Random effects:

 Formula:  ~ PA | INST

 Structure: General positive-definite

               StdDev   Corr

(Intercept) 6.1190489 (Intr)

     PRIORC 0.1645756 0.253

   Residual 1.0000000

 

 

Would anyone tell me what I am missing here? Clearly, the matrix is being transformed when summarized, but why and how?

 

Thanks a lot for your help

 

William

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