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High correlation among random effects for longitudinal model

Dear Stuart and Ben,

Thank you, this worked to significantly reduce the correlations between the
intercept and the linear and quadratic terms (though still quite high
between the linear and quadratic term):

Random effects:
 Formula: ~time + I(time^2) | student_ID
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev    Corr
(Intercept) 18.671959 (Intr) time
time        11.029842 -0.262
I(time^2)    8.359834 -0.506  0.959
Residual    29.006598

Could I ask if that correlation between the linear (time) and quadratic
I(time^2) terms is cause for concern - and if so, how to think about
(potentially) addressing this?
Josh
On Sun, Apr 1, 2018 at 12:34 PM Ben Bolker <bbolker at gmail.com> wrote: