[R-sig-ME] Residuals for a binomial lmer model

[Andy Fugard]

Sorry, that works modulo variable names...  Second try.

med = median(sleepstudy$Reaction)
sleepstudy$bin = (sleepstudy$Reaction > med) + 0
mod = lmer(bin ~ Days + (1|Subject) + (0+Days|Subject),
            data = sleepstudy, family = binomial)

ilog = function(x) { 1/(1 + exp(-x)) }
boxplot(ilog(fitted(mod)) ~ bin, data = sleepstudy)

Andy Fugard wrote:
> Hello,
> 
> I was wondering how to get residuals out of binomial lmers as the 
> "residuals" function isn't implemented.  I've noticed a few other people 
> ask the question too but get no response.  (Or at least I haven't found 
> a response.)
> 
> I guess the answer is just to use the "fitted" function, which is 
> implemented for binomial GLMMs.
> 
> Take the sleepstudy data, dichotomize Reaction (just to give us a 
> dataset), and fit a multilevel logistic model:
> 
> 
> med = median(sleepstudy$Reaction)
> sleepstudy$bin = (sleepstudy$Reaction > med) + 0
> M2 = lmer(bin ~ Days + (1|Subject) + (0+Days|Subject),
>            data = sleepstudy, family = binomial)
> 
> 
> We can pull out the fitted values and, say, plot fitted (post-inverse
> logit) against data using a boxplot:
> 
> 
> ilog = function(x) { 1/(1 + exp(-x)) }
> boxplot(ilog(fitted(fm3)) ~ bin, data = sleepstudy)
> 
> 
> Not sure now how useful this is, but I had some reason for wanting to peek!
> 
> Andy
> 


-- 
Andy Fugard, Postgraduate Research Student
Psychology (Room F3), The University of Edinburgh,
   7 George Square, Edinburgh EH8 9JZ, UK
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