Dear R-helpers...
I've be trying to run a variance analysis to compare means between various
lines in various treatments.
I have 10 genotypes (GEN), tested in 2 environments (ENV) and in each
environment there are 3 repetitions (REP). Several traits were recoded (yield,
flowering, plant height...)
First I checked whether the residuals were normally distributed and then the
homogeneity of variances.
For those which satisfied the assumptions for ANOVA, I performed aov. I tested
two models, one simple (GEN and ENV being fixed effects) and the other mixed
effects (REP)
aov1 <- aov (Y~GEN*ENV, data=mydata)
aov2 < - aov (Y~GEN*ENV+Error(REP/ENV, data=mydata)
When I wanted to compare the likelihood of these models, I failed performing
the extractAIC for the mixed model (aov2).
Is there any reason why extractAIC doesn't work in models including a random
effect?
As for other traits the assumption of homoscedasticity was violated I ran a lmer
When I ran the following model
lmer1 <- lmer(Y~GEN*ENV + (1|REP), data=mydata)
the following error message came
Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) :
contrasts can be applied only to factors with 2 or more levels
Could you please help me with this?
Thanks
Cecile
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