Hello,
is there a special package/method to cross-validate linear fixed effects and
mixed effects models (from lme)? I've tried cv.glm on an lme (hoping that it
may deal with any kind of linear model ...), but it raises an error:
Error in eval(expr, envir, enclos) : couldn't find function "lme.formula"
so I guess it's not dealing with an lme.
I've realized that removing randomly some lines from the data frame used for
lme strongly changes the the estimates and reduces the correlation between
fitted and actual values. Therefore I'd like to get a more "realistic" view of
the prediction performance.
Any ideas are welcome,
+thanks,
Arne
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