[R-sig-ME] GLMM linearity checking
fengsj at mail.utexas.edu
Thu Jun 3 19:10:59 CEST 2010
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 `$<-.data.frame`(`*tmp*`, "resid", value = c(-0.776415 :
replacement has 13580 rows, data has 68158
Is there any way to match residuals and the predictor?
I tried just plot(model), but it doesn't work for GLMM.
----- Original Message -----
From: "Ben Bolker" <bolker at ufl.edu>
To: <fengsj at mail.utexas.edu>
Cc: <r-sig-mixed-models at r-project.org>
Sent: Thursday, June 03, 2010 11:25 AM
Subject: Re: [R-sig-ME] GLMM linearity checking
> fengsj at mail.utexas.edu wrote:
>> I am sorry for asking this question here. It is more related to
>> logistic regression.
>> I need to use GLMM (binomial(link = "logit")) )to fit my data. The
>> dependent variable is 0 or 1 and I'd like to do some roughly
>> graphical checkings for my data to see if the responses of
>> transformaed data are linear with respect to continuous predictors in
>> general. How should I do this?
> how about
> m <- glmer(...,data=d)
> d$resid <- residuals(m)
> 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
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