R help - May 2006 - qu: predict with lmer (lme4) or other ways to get classification accuracy

Hi,

I am using lmer (from the package lme4) to predict a binary response
variable (REL) from a bunch of fixed effects and two random effects
(Speaker_ID and NPhead_lemma):

fit <- lmer(REL ~
	SPEAKER_GENDER +
	log(SPEECHRATE) +
	SQSPEECHRATE +
        .....
        + (1|Speaker_ID) + (1|NPhead_lemma),
	family="binomial",
	data=data.lmer,
	method="Laplace", model=T, x=T)

I would like to get classification accuracies for the derived model,
or even do some evaluation (cross-validation), but I cannot find a way
to get to the predicted values. As far as I can tell no predict method
has been implemented for lmer, right? I also was trying to figure out
whether lmer stores the predicted values somewhere (I read the
documentation and implementation summary,
/library/lme4/doc/Implementation.pdf).

Many thanks for your help and my apologies if I overlooked something
really simple.

Florian

--
T. Florian Jaeger
Ph.D. student
Linguistics Department,
P: +1 (650) 725 2323
F: +1 (650) 723 5666
U: http://www.stanford.edu/~tiflo/

Checking 'help("lmer")' leads me also to
'help("lmer-class")', both
of which are helpful.  Unfortunately, I know of no general "predict" 
method that's available for an object of class 'lmer'.  A
preliminary
function of that nature is as follows:


predict.lmerBin <- function(object, X){
# object has class "lmer"
# X = model matrix with columns
#     matching object at X
   if(missing(X))
     X <- object at X
#
   b <- fixef(object)
   X %*% b
}


	  ## To use this, you need to know how to use
# 'preduct.glm'.

# Example using data(Contraception), discussed in
(mlmR <- vignette("MlmSoftRev")) # opens in Adobe Acrobat
# To open a script file companion to vignette("MlmSoftRev")
#edit(mlmR) # with Rgui
#Stangle(mlmR$file) # with ESS

fitBin <- lmer(use ~ urban+age+livch+(1|district),
                Contraception, binomial)
predict.lmerBin(fitBin)

	  Does this answer your question?
	  Spencer Graves
p.s.  If your example had been simple and self-contained, it would have 
been to reply, because I could copy a few lines of R code from your 
email into R, tested a few ideas, and craft a reply in a very few 
minutes, if not seconds.  Without that, crafting a sensible reply takes 
more time, partly because it's less clear what you need to know to move 
to the next step, and partly because after I guess what you are really 
asking, I must next hunt for a suitable example.

T. Florian Jaeger wrote:
> Hi,
> 
> I am using lmer (from the package lme4) to predict a binary response
> variable (REL) from a bunch of fixed effects and two random effects
> (Speaker_ID and NPhead_lemma):
> 
> fit <- lmer(REL ~
> 	SPEAKER_GENDER +
> 	log(SPEECHRATE) +
> 	SQSPEECHRATE +
>         .....
>         + (1|Speaker_ID) + (1|NPhead_lemma),
> 	family="binomial",
> 	data=data.lmer,
> 	method="Laplace", model=T, x=T)
> 
> I would like to get classification accuracies for the derived model,
> or even do some evaluation (cross-validation), but I cannot find a way
> to get to the predicted values. As far as I can tell no predict method
> has been implemented for lmer, right? I also was trying to figure out
> whether lmer stores the predicted values somewhere (I read the
> documentation and implementation summary,
> /library/lme4/doc/Implementation.pdf).
> 
> Many thanks for your help and my apologies if I overlooked something
> really simple.
> 
> Florian
> 
> --
> T. Florian Jaeger
> Ph.D. student
> Linguistics Department,
> P: +1 (650) 725 2323
> F: +1 (650) 723 5666
> U: http://www.stanford.edu/~tiflo/
> 
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