Problematic correlations between random effects
On Thu, 23 Feb 2012, Leite,Walter wrote:
Folks,
I fitted a model with several random effects to data with a
cross-classification of students and schools using lmer. Two random
effects have correlation of -1 and others near 1, as shown below. I
thought that this would only occur if any random effects were not
necessary in the model, but I built this model adding the random effects
one at a time and comparing the fit with BIC and AIC. Also, none of the
variances are very small. Could someone advise me on why these
correlations occurred and ways I can solve this problem?
Random effects:
Groups Name Variance Std.Dev. Corr
CHILDID (Intercept) 333.63787 18.26576
time.period 7.99838 2.82814 -1.000
I(time.period^2) 11.16830 3.34190 -0.514 0.514
I(time.period^3) 0.31869 0.56453 -0.189 0.189 0.938
School_ID (Intercept) 87.59255 9.35909
time.period 33.30370 5.77094 0.093
I(time.period^2) 1.48008 1.21659 -0.171 0.960
Residual 39.94649 6.32032
Number of obs: 11960, groups: CHILDID, 2990; School_ID, 996
Have you centred time.period? My simple minded understanding is that polynomial terms like that will always be highly correlated unless you orthogonalize them, but the LR based criteria will still guide you correctly.
| David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v