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List:       r-sig-mixed-models
Subject:    [R-sig-ME] Different number of observations in variables of glmer
From:       "Cueva, Jorge" <jorge.cueva () tum ! de>
Date:       2018-06-13 15:35:21
Message-ID: 831d663cb2094d7d9e354fe1fe4b8276 () tum ! de
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Hello, I am trying fit a glmer where the fixed variables has a different number of \
observations (72 and 60). With the models where the variables has the full \
observations I donīt have problems but yes in the models where some of its variables \
has 60 observations. In the second case,  all work well until I compute the R2m and \
R2c and I get the error "fitting model with the observation-level random effect term \
failed. Add the term manually", so, when I ingress the observation level the AIC \
increase 2 points, and miss 1 df. Please how I might work in these cases??

First case...
glmer(Spp~1+Mth.Prec+Soil.depth+Drainage+(1|Cluster),data = \
VariabRL,family=poisson,glmerControl(optimizer="bobyqa", optCtrl = list(maxfun = \
2e5)))

Second case...
glmer(Spp~1+Mth.Prec+Soil.depth+Drainage+(1|Cluster)+(1|X),data = \
VariabRL,family=poisson,glmerControl(optimizer="bobyqa", optCtrl = list(maxfun = \
2e5)))

Mth.Prec = 72 observations
Soil.depth and Drainage = 60 observations
X = observation level

Thanks a lot

Jorge Cueva Ortiz
Ing. Forestal
ECU: 0993085161
GER: 0049 1631327886


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