[R-sig-ME] NAs from lmList(fit GLM) :fit fixed-effect GLMs within each level of the random factors

[fengsj at mail.utexas.edu]

I just read about:” No definition of residuals is completely  
satisfactory for binary data (in GLM)”.  Does anyone know how to check  
linearity for GLM(M) with the binary data?
Thanks


Quoting fengsj at mail.utexas.edu:

> I use lmList to fit GLM (logit, with 3 contious predictors) within each
> leavel of my random factor. I can get results but with some warnings. I
> think the reason for the warnings is because GLM(logit) can not be used
> or estimated within some levels. (The dependents are all 0 within some
> levels. There are some NA for some estimated coefficients in the
> results).
> Is there a way to remove those lm objects with NA values from the
> lmList results? I cannot use plot(),intervals() for the lmList
> results(I guess it is because of those NAs )
> Thanks!
>
>
>
>
> Quoting David Atkins <datkins at u.washington.edu>:
>
>>
>> Ben et al.--
>>
>> Methinks lmList() in lme4 package takes a family argument:
>>
>> Arguments
>>
>> formula 	a linear formula object of the form y ~ x1+...+xn | g. In the
>> formula object, y represents the response, x1,...,xn the covariates,
>> and g the grouping factor specifying the partitioning of the data
>> according to which different lm fits should be performed.
>>
>> data 	a data frame in which to interpret the variables named in object.
>>
>> family 	an optional family specification for a generalized linear model.
>>
>> [snip]
>>
>> So, I don't think a workaround is needed.
>>
>> cheers, Dave
>>
>> -- 
>> Dave Atkins, PhD
>> Research Associate Professor
>> Department of Psychiatry and Behavioral Science
>> University of Washington
>> datkins at u.washington.edu
>>
>> Center for the Study of Health and Risk Behaviors (CSHRB)
>> 1100 NE 45th Street, Suite 300
>> Seattle, WA  98105
>> 206-616-3879
>> http://depts.washington.edu/cshrb/
>> (Mon-Wed)
>>
>> Center for Healthcare Improvement, for Addictions, Mental Illness,
>>  Medically Vulnerable Populations (CHAMMP)
>> 325 9th Avenue, 2HH-15
>> Box 359911
>> Seattle, WA 98104?
>> 206-897-4210
>> http://www.chammp.org
>> (Thurs)
>>
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