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GLMM linearity checking

3 messages · fengsj at mail.utexas.edu, Ben Bolker, Shujuan Feng

Original
fengsj at mail.utexas.edu
# 
I am sorry for asking this question here. It is more related to  
logistic regression.

I need to use GLMM (binomial(link = "logit")) )to fit my data. The  
dependent variable is 0 or 1 and  I'd like to do some roughly  
graphical checkings for my data to see if the responses of  
transformaed data are linear with respect to continuous predictors in  
general. How should I do this?

Thanks,
Ben Bolker
#
fengsj at mail.utexas.edu wrote:
how about

 m <- glmer(...,data=d)
 d$resid <- residuals(m)

 xyplot(resid~continuous_predictor_1,type=c("p","smooth"),data=d)

 ...

  Non-linearity on the transformed scale will appear as a (non-flat)
pattern of the (smoothed line fitted to the) residuals as a function of
the continuous predictors ...

  Ben Bolker
Shujuan Feng
# 
Thanks so much!

I read about Graphical checking for GLMM (transformed by the link Function) 
before fitting the model from a paper. I have difficulty in imaging how the 
0s and 1s are transformed by the ink. .....

I tried your suggestions and this way should give me more valuable checkings 
for the model. But because I have a lot of missing data, I could not put the 
residuals into the data. I got errors:

Error in `$<-.data.frame`(`*tmp*`, "resid", value = c(-0.776415  : 
replacement has 13580 rows, data has 68158

Is there any way to match residuals and the predictor?

I tried just plot(model), but it doesn't work for GLMM.



Thanks!!







----- Original Message ----- 
From: "Ben Bolker" <bolker at ufl.edu>
To: <fengsj at mail.utexas.edu>
Cc: <r-sig-mixed-models at r-project.org>
Sent: Thursday, June 03, 2010 11:25 AM
Subject: Re: [R-sig-ME] GLMM linearity checking