[prev in list] [next in list] [prev in thread] [next in thread] 

List:       r-sig-mixed-models
Subject:    [R-sig-ME] Convergence failure in lmer
From:       Bob Patrick <bb.patrick () hotmail ! com>
Date:       2010-02-17 19:53:14
Message-ID: BAY142-W27557BA5340E1D49ED9D4597480 () phx ! gbl
[Download RAW message or body]


Hi there R-users,
 
I have relative abundance data for 13 mammal species that I collected at various \
sites that ranged  in road density. I'm trying to determine the effect of road \
density on animal abundance across body sizes.  For most species, I have data that \
was collected in one year but for a few species I have two years of  complete data, \
to account for this I nested year (as a factor) within body size (also a factor). I'm \
trying to  run three models in lmer; random intercept, random slope and random \
intercept and slope (see below), and then  use AIC/BIC to select the best model. My \
first question is, have I coded these models correctly?

random intercept:

M1<-lmer(Log_Abundance ~ Log_RoadDensity + (1|fBodySize/fYear), data=mixed)

random slope:

M2<-lmer(Log_Abundance ~ Log_RoadDensity + (0+Log_RoadDensity |fBodySize:fYear), \
data=mixed)

random effects intercept and slope:

M3<-lmer(Log_Abundance ~ Log_RoadDensity + \
(Log_RoadDensity|fBodySize/fYear),data=mixed)


And second, when running the random intercept and slope model, it fails to converge. \
I have tried  increasing the maximum number of iterations with \
(control=list(maxIter=1000)) but it still won't converge. Does  anyone have any \
suggestions?

Thank you,

Bob




 		 	   		  
_________________________________________________________________


	[[alternative HTML version deleted]]

_______________________________________________
R-sig-mixed-models@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models


[prev in list] [next in list] [prev in thread] [next in thread]