Fixing heteroscedasticity in mixed-effects model?

Ben Bolker · 2012-03-29T19:41:42Z

Malin Pinsky writes: > I'm having problems fitting a mixed-effects model for an ecological > meta-analysis, and I'm curious if anyone has advice. In particular, > it's pretty clear that the variance in the residuals increases with > the predicted mean, but my normal fixes don't seem to be working. The > model is: > > mod1 > where Cd is a drag coefficient (>0 before log-transformation), Re is a > physic

Ben Bolker

Thu, Mar 29, 2012 12:41 PM

Malin Pinsky <malin.pinsky at ...> writes:

[big snip to make gmane happy]

Probably.

  A quick answer is that you should able to incorporate heteroscedasticity
in lme (from the nlme function) via something like weights=varPower():

mod1 <- lme(logCd ~ logRe*Hab, random=~logRe|Study, data=temp,
   weights=varPower())

(this might not be quite right, you might want to read ?nlme::varPower
and/or the relevant bit of Pinheiro and Bates 2000)

  If you want to go the Gamma route, you can try (1) the development
version of lme4 (install from r-forge, but it might be broken right
now ...); (2) glmmADMB ...

  ... but I would probably suggest lme for now.

Fixing heteroscedasticity in mixed-effects model?

Thread (2 messages)