[R-sig-ME] How to extract num. of observations and groups used in a mixed model using gee package

[Ben Bolker]

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On 12-04-24 12:11 PM, david oseguera montiel wrote:
> Ben, Rob and David, Thank you all, to resume, the option given by
> Ben worked when id variable is stored like in the sleeping data
> set.
> 
> library(lme4) mod <- gee(Reaction ~ Days, id=Subject,
> data=sleepstudy, corstr="exchangeable") length(unique(mod$id)) [1]
> 18
> 
> The option given by David worked when id variable is stored like in
> the warpbreaks data set.
> 
> 
> summgee <- summary(gee(breaks ~ tension, id=wool, data=warpbreaks, 
> corstr="exchangeable"))
> 
> summgee$call$id # wool 
> length(levels(warpbreaks[[as.character(summgee$call$id)]])) #[1] 2
> 

  This is the difference between a 'gee' object and 'summary.gee'
object.  Please make sure to read the details quoted below, to make
sure that you are not misled in cases where the clusters are coded as
non-unique (but contiguous) levels ... (and it wasn't my idea, it was
Chuck Cleland's).

  Ben

> 
> On 24/04/2012 10:01, Ben Bolker wrote:
>> On 12-04-24 10:54 AM, Robert Kushler wrote:
>>> The following lines from the gee help page ...
>>> 
>>> Details
>>> 
>>> Though input data need not be sorted by the variable named
>>> "id", the program will interpret physically contiguous records
>>> possessing the same value of id as members of the same cluster.
>>> Thus it is possible to use the following vector as an id vector
>>> to discriminate 4 clusters of size 4:
>>> c(0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1).
>>> 
>>> 
>>> ... indicate that the proposed strategy may not yield a
>>> correct answer.  In fact, the above suggests that you could get
>>> different results depending on whether or not your data set is
>>> sorted.  I find this quite disturbing, but haven't taken the
>>> time to test it.
>>> 
>>> Regards,   Rob Kushler
>> Yow.  Good catch.
>> 
>> Maybe length(rle(geemodel$id)$length) would work?
>> 
>> 
>>> (id<- rep(c(0,1,0),each=3))
>> [1] 0 0 0 1 1 1 0 0 0
>>> length(rle(id)$lengths)
>> [1] 3
>>> (id<- rep(c(0,1,0,1),each=3))
>> [1] 0 0 0 1 1 1 0 0 0 1 1 1
>>> length(rle(id)$lengths)
>> [1] 4
>> 
>>> 
>>> 
>>> 
>>> 
>>> On 4/24/2012 10:25 AM, David Winsemius wrote:
>>>> On Apr 24, 2012, at 9:46 AM, Ben Bolker wrote:
>>>> 
>>>>> david oseguera montiel<oseguera.david at ...>  writes:
>>>>> 
>>>>>> I meant the grouping factor in the model indicated by id.
>>>>>> From gee documentation 'id = a vector which identifies
>>>>>> the clusters..'. So in the warpbreaks data set, id = wool
>>>>>> has 54 obs, in two clusters (groups).
>>>>> [snip]
>>>>> 
>>>>>>>> David, Thank you very much. Number of observations
>>>>>>>> solved, but I am still missing how to find out the
>>>>>>>> number of groups used. In the warpbreaks data set
>>>>>>>> these are 2. Any ideas. Thank you.
>>>>>>>> 
>>>>>>> I must be unclear what you mean by "number of groups".
>>>>> 
>>>>> Didn't Chuck Cleland's answer work, i.e.
>>>>> length(unique(model$id)) ... ?
>>>> It didn't work for me. length(unique(summgee$id)) [1] 0
>>>>> summgee$id
>>>> NULL
>>>> 
>>>> See my other reply for what did work. I suppose it could be
>>>> that both the OP and I are behind on gee versions. Mine is 
>>>> 4.13-17 and I see that there is a more recent binary on CRAN.
>>>> With a (slightly out-of-date) version loaded, I am loath to
>>>> detach because getting things to all sync up is a bit of a
>>>> hassle and error-prone without a fresh start and I have other
>>>> work time-consuming running in this session.
>>>> 
> 

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