hello everyone,
I'm modelling in lmer an average chick weight defined as
"Total.brood.mass ~ offset(chick.number), with three fixed and two
random effect. Next, I want to use function dredge from MuMIn package
for model averaging. Not sure why, but in consequence the offset
variable is treated as a predictor, so I get a table that mixes models
with and without that offset term (the first crosses to the right):
Model selection table
(Int) all.rLD bng INF all.rLD:bng all.rLD:INF bng:INF
all.rLD:bng:INF off(log.fld) df logLik AICc delta
256 75.70 -0.6761 + + + + + +
+ 11 -801.906 1627.4 0.00
168 75.44 -1.1670 + + +
+ 8 -805.477 1627.8 0.43
184 75.68 -0.7785 + + + +
+ 9 -804.390 1627.8 0.46
192 75.65 -0.8870 + + + + +
+ 10 -803.651 1628.6 1.22
176 75.40 -1.2690 + + + +
+ 9 -804.832 1628.7 1.35
152 76.25 -0.7686 + + +
+ 8 -807.367 1631.6 4.21
136 76.13 -1.1860 + +
+ 7 -808.533 1631.7 4.35
128 77.34 -0.6853 + + + + + +
11 -804.083 1631.7 4.35
56 77.33 -0.7899 + + + +
9 -806.572 1632.2 4.83
40 77.08 -1.1880 + + +
8 -807.687 1632.2 4.84
160 76.16 -0.8849 + + + +
+ 9 -806.607 1632.3 4.90
144 76.06 -1.2960 + + +
+ 8 -807.871 1632.6 5.21
When I try to use a subset function, I get an error:
> offavg<-dredge(avgch, subset=offset(log.fledge))
Error in offset(log.fledge) : object 'log.fledge' not found
In addition: Warning messages:
1: In dredge(avgch, subset = offset(log.fledge)) :
comparing models fitted by REML
2: In dredge(avgch, subset = offset(log.fledge)) :
not all terms in 'subset' exist in 'global.model'
So, how do I get a table with offset models only? Not sure if I define
something incorrectly or maybe there's a different way to get around
that? Will appreciate any suggestions
cheers,
Kasia
Katarzyna Kulma
PhD Student
Department of Ecology and Genetics
Institute of Ecology and Evolution/Animal Ecology
Uppsala University
Norbyvägen 18D
SE-752 36 Uppsala, Sweden
email: katarzyna.ku...@ebc.uu.se
Tel.+46 (0)18 471 2672
Fax.+46 18 471 6484
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