Have you considered "VarCorr"? I've used it with "lme", and the
documentation in package lme4 suggests it should work with GLMM, which
might also do what you want from glmmPQL.
hope this helps. spencer graves
Stephen Ellner wrote:
For a Monte Carlo study I need to extract from an lme model
the estimated standard deviation of a random effect
and store it in a vector. If I do a print() or summary()
on the model, the number I need is displayed in the Console
[it's the 0.1590195 in the output below]
print(fit)
Linear mixed-effects model fit by maximum likelihood
Data: datag2
Log-likelihood: -145.0028
Fixed: lst1 ~ lst
(Intercept) lst
1.1080629 0.7582595
Random effects:
Formula: ~1 | yeart
(Intercept) Residual
StdDev: 0.1590195 0.3313497
However I have not been able to find that number anywhere in the
model object returned by lme. Can anyone tell me how to pull it
or compute it from a model returned by lme? Ditto for models with
random intercept fitted by glmmPQL with family=binomial.
Details:
The relevant data are the first 3 colums from the
data frame extracted below. Yeart is a factor (year of
study) ranging from 1 to 16. The model is linear regression of
lst1 on lst with constant slope, random intercept varying
across years. I'm using R 1.9.1 in WinXP and the current
version of nlme from CRAN.
Code:
datag2=groupedData(lst1~1|yeart,data=cdata);
mixed.grow=lme(fixed=lst1~lst,random=~1, method="ML",data=datag2);
mixed.surv=glmmPQL(fixed=surv~lst, random=~1|yeart, family=binomial,
data=cdata,niter=50);
Some of the data:
yeart lst lst1 surv flow
1 1 3.158088 3.331216 1 0
2 1 2.472618 2.486410 1 0
3 1 3.582950 3.417807 1 0
4 1 3.554819 3.377117 1 0
5 1 2.830049 2.992426 1 0
6 1 2.779616 3.240449 1 0
7 1 2.580484 2.930154 1 0
Thanks in advance,
Steve
Stephen P. Ellner ([EMAIL PROTECTED])
Department of Ecology and Evolutionary Biology
Corson Hall, Cornell University, Ithaca NY 14853-2701
Phone (607) 254-4221 FAX (607) 255-8088
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