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st: glm for binomial regression with


From   "Airey, David C" <david.airey@vanderbilt.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: glm for binomial regression with
Date   Wed, 20 Apr 2011 13:46:08 -0500

.

I see the cloglog link in xtgee, and I have just one level of clustering, so this is a possibility.

> I have questions about binomial regression.
> 
> On page 527 of the Stata 11 -glm- help in the [R] base reference PDF manual is described in Example 2 a binomial data set which describes the death of beetles for a dose response experiment (ldose = log dose, n = total number of beetles, r = number dead):
> 
> . list , clean
> 
>        ldose    n    r  
>  1.   1.6907   59    6  
>  2.   1.7242   60   13  
>  3.   1.7552   62   18  
>  4.   1.7842   56   28  
>  5.   1.8113   63   52  
>  6.   1.8369   59   53  
>  7.    1.861   62   61  
>  8.   1.8839   60   60 
> 
> The data is modeled by:
> 
> glm r ldose, family(binomial n) link(logit)
> 
> or
> 
> glm r ldose, family(binomial n) link(cloglog)
> 
> where the cloglog links allows the dose curve to be asymmetric. In these data the cloglog link fits better than the logit link.
> 
> I have data like the above, except with replications at each dose.
> 
> The manual also says the data could be analyzed by expanding the data and using -logit- (if the logit link was the better fit).
> 
> I have two questions.
> 
> Unlike the data above, I have replications for each dose. Is this -xt- or clustered data?
> 
> The data above are already grouped and beetles are replicates, but we have:
> 
> . list , clean
> 
>        ldose    n    r  
>  1.   1.6907   59    6  
>  2.   1.6907   62    5  
>  3.   1.6907   62   10  
>  4.   1.6907   59    3  
>  etc. 
> 
> I could ignore the potential clustering and simply model n = 59+62+62+59 and r = 6+5+10+3. I guess it depends on how the experiment is actually done, and I could test for clustering too.
> 
> My second question, however, is if I were to expand the data above that included a replication by dose (with appropriate replicate id variable included as the cluster id), I could analyze this using xtlogit or xtmelogit---but how do you do this if you want asymmetry, like you get with glm and the cloglog link? Is that available in glm but not xt models in Stata?
> 
> -Dave

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