I have two questions I would appreciate help with if possible. My first
question:
I have used nlsList to create an object that I then update using nlme to
apply a function for exponential growth to a grouped data object. The
function is:
fExpIncrease <- function(x, int, B) int*(exp( B* x))
My question involves the correlation of the random effects when both the
int and B terms above are included in the model as "random = int + B ~
1" ; they are extremely correlated (0.994), and the model is fairly
unstable as the random effects are alternately dropped. However, using
augPred to look at the results appears to suggest that the predictions with
both in the model are better fit, and theoretically I can make a case for
both random effects. Examining the model with intervals shows that both
random effects are bounded away from 0, but their correlation is not, but
is not, in fact it runs from -.999 to 1.
My question, is it inappropriate to leave both random effects in under
these circumstances relative to their correlation ?
My second question involves a problem which arose when I tried to center
the observations in an attempt to reduce this correlation, and I will post
it separately.
Thanks,
Buzz Burhans
Department of Animal Science
Cornell University
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