Re sidual variance in lmer
Hello everybody, using the lmer function, I have fitted the following logistic mixed regression model on an experimental data set containing one fixed factor (Cond) and three random variables (Sito, Area, Trans):
model<-lmer(Caul~Cond+(1|Sito)+(1|Area)+(1|Trans), data=dataset, family=binomial)
this is the output:
summary(model)
Generalized linear mixed model fit by the Laplace approximation Formula: Caul ~ Cond + (1 | Sito) + (1 | Area) + (1 | Trans) Data: dataset AIC BIC logLik deviance 548.7 573.7 -268.3 536.7 Random effects: Groups Name Variance Std.Dev. Trans (Intercept) 3.2313398 1.797593 Area (Intercept) 0.0000000 0.000000 Sito (Intercept) 0.0047151 0.068667 Number of obs: 480, groups: Trans, 48; Area, 12; Sito, 2 As you can see the residual variance is missing. Can anybody tell me why? Does anybody know how can I get it? Thank you for your attention, I wish somebody can help me. Have a nice day, best regards, Tommaso Alestra
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