[R] Relevel() catagorical variables in a GLM

David Winsemius dwinsemius at comcast.net
Sun May 29 14:48:56 CEST 2011 

On May 29, 2011, at 5:10 AM, ashley wrote:

> Thanks Josh,
>
> This makes sense. The coefficient of one parameter is given in  
> reference to
> another parameter. (Aha! The "reference" parameter.)
>
> I'm still a little confused on the standard errors (SEs) and why  
> they change
> too? Should I change the reference around until I find the best- 
> looking SEs?
> Somehow that doesn't seem right...

If you choose a reference level that only has a few members, then all  
the comparisons will reflect that data situation, i.e. the standard  
errors for any contrast with a groups with scanty numbers will be large.
>
> I am trying to eventually make statements like:
> "Fish A showed a weak, yet positive, response to HS and the low SE  
> gives us
> confidence in this association"

I didn't see any contrasts in your models that merited that  
representation. In general, you should be using likelihood ratio tests  
for inference, rather than Wald tests. The example you provide is one  
good illustration why that is so.

-- 
David.

> "Fish A showed a weak negative response to SH and the low SE gives us
> confidence in this association (though less confidence than for HS)"
> "Fish A showed a strong negative response to SS, however the SE is  
> very high
> so we cannot say this with high certainty"
>
> Do these sound like an accurate reflection of what the output is  
> saying? (I
> know that "low SE" is arguable but...)
>
> So then the SE for HH 923.60 (2nd run) or 0.2781 (1st run)?
>
> Thank you!
> Ashley
>
>
> On Sat, May 28, 2011 at 11:49 PM, Joshua Wiley-2 [via R] <
> ml-node+3558477-671379230-241127 at n4.nabble.com> wrote:
>
>> Hi Ashley,
>>
>> It does not look like you have done the wrong thing to me.  The
>> results will be different because eacho f the parameter estimates is
>> now the change from SS to ___ instead of from HH to ____.  In fact,
>> from your first table, you can calculate all the parameters in the
>> second.  The intercept for SS as reference is:
>>
>> (-5.2671) + (-18.2990) = -23.5661
>>
>> the difference between SH and SS is:
>>> (-0.5736) - (-18.2990)
>> [1] 17.7254
>>
>> which is now the parameter estimate for SH in the SS as reference
>> model.  You could go on in like fashion for the rest.
>>
>> HTH,
>>
>> Josh
>>
>> On Sat, May 28, 2011 at 4:27 PM, ashley <[hidden email]<http://user/SendEmail.jtp?type=node&node=3558477&i=0 
>> >>
>> wrote:
>>
>>> Hello list readers,
>>>
>>> I am running a set of GLMs on fish spp presence/absence as a  
>>> function of
>>> various habitat characteristics. My response is binomial and I  
>>> have four
>>> predictors, three of which are categorical.
>>>
>>> So, R takes one of my predictor-variables away to use as the  
>>> intercept
>> (the
>>> first one alphabetically). However, I want to know the coefficient  
>>> and SE
>> of
>>> this predictor. I tried relevel() and reran the model. Abbreviated
>> summary()
>>> results for each run are below. The results seem drastically  
>>> different.
>> Have
>>> I done the wrong thing?
>>>
>>> (Below is a result from the model with only one predictor, to save  
>>> space
>> and
>>> hassle.)
>>>
>>> Thanks,
>>> Ashley
>>>
>>> #Default reference level = HH:
>>>
>>>                                Estimate Std. Error z value Pr(>|z|)
>>> (Intercept)                     -5.2671     0.2781 -18.942    
>>> <2e-16 ***
>>> raw.table$SubsComboHS    0.8127     0.6438   1.262    0.207
>>> raw.table$SubsComboSH  -0.5736     1.0393  -0.552    0.581
>>> raw.table$SubsComboSS -18.2990   923.6023  -0.020    0.984
>>>
>>> #Command used to change reference level:
>>>> raw.table$SubsCombo<-relevel(raw.table$SubsCombo, ref="SS")
>>>
>>> #New reference level = SS:
>>>
>>>                                  Estimate Std. Error z value Pr(>| 
>>> z|)
>>> (Intercept)                     -23.57     923.60  -0.026    0.980
>>> raw.table$SubsComboHH    18.30     923.60   0.020    0.984
>>> raw.table$SubsComboHS    19.11     923.60   0.021    0.983
>>> raw.table$SubsComboSH    17.73     923.60   0.019    0.985
>>>
>>>
>>>
>>> --
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>>
>>
>>
>> --
>> Joshua Wiley
>> Ph.D. Student, Health Psychology
>> University of California, Los Angeles
>> http://www.joshuawiley.com/
>>
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>
>
>
> -- 
> **Please note new extension
> _____________________________________________
>
> Ashley Knight
> Rote Program Assistant
> Research Assistant
> Institute for Applied Marine Ecology, CSU Monterey Bay
> Chapman Science Academic Center (Bldg 53)
> 100 Campus Center, Seaside, CA 93950
>
> (831) 582-4522
> aknight at csumb.edu
> http://sep.csumb.edu/ifame
> _____________________________________________
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David Winsemius, MD
West Hartford, CT

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