[R] using residuals of binomial GLM

Yuval Sapir sapiryuval at gmail.com
Tue Mar 24 15:02:41 CET 2009

Hi all,
This is more a question in statistics, but I hope to get also the R 
practice for my question:
I have an ancova model where the response variable is flowering (plant 
has a flower = 1, no flower = 0). The explanatory variables are leaf 
length, leaf thick (both continuous variables), and soil type (factorial 
with three levels):
 > model<-glm(flower~(thick+length)*soil,family="binomial")
In the aov summary I find a significant effect of all variables, and a 
significant interaction between thick and soil, so I want to explore 
this interaction after "cleaning" the effect of length. I thought of two 
possible ways to extract the residuals:
 > res.thick<-resid(update(model,~.-thick-soil-thick:soil))
 > res.thick<-resid(glm(flower~length+length:soil,family="binomial"))
I validated that the two methods give the same results. Anyhow, now I 
want to compare the effect of thick on flowering probability,separately 
for each soil. But the residuals extracted are not 0 or 1 anymore.  
Linear glm, such as
 > model1<-glm(res.thick1~thick*soil)
doesn't seem to be right, and, moreover, I am interested in the 
estimated coefficients and their interpretation (say - plotting a 
meaningful graph). How can I get a logistic regression from residuals? 
Do I NEED logistic regression? How should I understand the coefficients 
I get in summary of the residuals model? How can I use the results of 
the residuals model for plotting the separate lines for the probability 
(logistic) curve?
Thanks in advance

Yuval Sapir, PhD
Porter School of Environmental Studies
Dept. of Plant Sciences
Tel Aviv University, Tel Aviv, 69978 Israel
Mobile:054-7203140; Lab: 03-6405877


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