Dear users,
 
After more than a day figuring out why my predicted values were so high we found out that fitting a term as poly(my_term,1)
was creating havoc in the fixed effects of LMER for this term.
 
I thought that poly(my_term,1) was the same that fitting "my_term", it seems that I was wrong.
 
Although it doesn't make sense fitting a linear term as poly(my_term,1) rather than the more economical "my_term", I wonder what it is behind
the poly( ) function that produces such a different result (see below). 
 
Many thanks
 
Javier
 
Model 1
fm1<-lmer(niche_breadth~cos_days+sin_days+poly(easting,2)+poly(northing,2)+
          poly(mean_temp,1)+lgdensity+lgdensity*poly(easting,2)+lgdensity*poly(northing,2)+
          (lgdensity|block)+(1|year),data=data)
 
 
fixef(fm1)[8]
poly(mean_temp, 1) 
         0.1789691 
Model 2 (as Model 1 but "mean_temp" rather than "poly(mean_temp,1)")
 
fixef(fm1)[8] ##all other fixed effects were as in Model 1.
   mean_temp 
2.590413e-05 
 
 
Dr. Javier Perez-Barberia
Population and evolutionary ecologist
The Macaulay Institute
Craigiebuckler
Aberdeen 
AB15 8QH
Scotland, UK

Tel: +44(0)1224 395221
e-mail: j.perez-barberia@macaulay.ac.uk
http://www.macaulay.ac.uk
http://www.macaulay.ac.uk/upland

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