Hi,
I was wondering if I might be able to ask some advice about doing residual
plots for the lmer function in the lme4 package.
Our group's aim is to find if the expression staining of a particular gene
in a sample (or "core") is related to the pathology of the core.
To do this, we used the lmer function to perform a logistic mixed model
below. I apologise in advance for the lack of subscripts.
logit P(yij=1) = â0 + Ui + â1Patholij where Ui~N(0, óu2),
i indexes patient, j indexes measurement, Pathol is an indicator variable
(0,1) for benign
epithelium versus cancer and yij is the staining indicator (0,1) for each
core where yij equals 1 if the core stains positive and 0 otherwise.
(I have inserted some example R code at the end of this message)
I was wondering if you knew how I could test that the errors Ui are normally
distributed in my fit. I am not familiar with how to do residual plots for
a mixed logistic regression (or even for any logistic regression!).
Any advice would be greatly appreciated!
Thanks and Regards
Marg
Example code:
lmer(Intensity.over2.hyp.canc~Pathology + (1|Patient.ID), data=
HSD17beta4.hyp.canc, family="binomial", na.action="na.omit")
#Family: binomial(logit link)
# AIC BIC logLik deviance
# 414.1101 431.4147 -203.0550 406.1101
#Random effects:
# Groups Name Variance Std.Dev.
# Patient.ID (Intercept) 4.9558 2.2262
# of obs: 559, groups: Patient.ID, 177
#Estimated scale (compare to 1) 0.6782544
#Fixed effects:
# Estimate Std. Error z value Pr(>|z|)
#(Intercept) -2.05734 0.24881 -8.2686 < 2.2e-16 ***
#PathologyHyperplasia -1.76627 0.44909 -3.9330 8.389e-05 ***
NB. Intensity.over2.hyp.canc is the staining of the core (ie 0 or 1)
Pathology is Hyperplasia or Cancer
Dr Margaret Gardiner-Garden
Garvan Institute of Medical Research
384 Victoria Street
Darlinghurst Sydney
NSW 2010 Australia
Phone: 61 2 9295 8348
Fax: 61 2 9295 8321
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