Testing whether I need a random effect?
On 08/17/2010 07:34 PM, Ben Bolker wrote:
Christopher David Desjardins wrote:
Hi I have the following model:
m.f<- glmer(NumCitations ~ 1 + Program + ProductType + ProductField +
(1 | ProductDate), family="poisson",data = data)
And I am wondering how I can test whether or not ProductDate needs to
be included as a random effect or if I could just run a glm() without
ProductDate?
see http://glmm.wikidot.com/faq , "How can I test whether a random effect is significant?" (there aren't worked examples there -- anyone want to donate some?)
Thanks Ben.
The library RLRSim and the function exactRLRT(). However, when I run
that function I get the following message:
> exactRLRT(m.f)
Using restricted likelihood evaluated at ML estimators.
Refit with method="REML" for exact results.
Error in if (rlrt.obs != 0) { : missing value where TRUE/FALSE needed
Does this function not work with the glmer() and the Poisson family?