[R] Compare lm() to glm(family=poisson)

Ronggui Huang ronggui.huang at gmail.com
Sun Aug 2 12:26:48 CEST 2009


In practices, it is not easy to make such decision. One example is
size of social ties in social network study. It is very common to use
OLS thought it is count variable rather than normal. I think AIC is
suggestive as well.

Ronggui

2009/8/2 Alain Zuur <highstat at highstat.com>:
>
>
>
> Mark Na wrote:
>>
>> Dear R-helpers,
>> I would like to compare the fit of two models, one of which I fit using
>> lm()
>> and the other using glm(family=poisson). The latter doesn't provide
>> r-squared, so I wonder how to go about comparing these
>> models (they have the same formula).
>>
>> Thanks very much,
>>
>> Mark Na
>>
>>       [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
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>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>
> The decision which distribution to use (Normal versus Poisson) should be an
> a priori choice. If you really want to compare them, then inspect the
> residuals of both models and see which model doesn't have any residual
> patterns.
>
> Alain
>
> -----
> --------------------------------------------------------------------
> Dr. Alain F. Zuur
> First author of:
>
> 1. Analysing Ecological Data (2007).
> Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
>
> 2. Mixed effects models and extensions in ecology with R. (2009).
> Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer.
>
> 3. A Beginner's Guide to R (2009).
> Zuur, AF, Ieno, EN, Meesters, EHWG. Springer
>
>
> Statistical consultancy, courses, data analysis and software
> Highland Statistics Ltd.
> 6 Laverock road
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> Email: highstat at highstat.com
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>
>
> --
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>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>



-- 
HUANG Ronggui, Wincent
PhD Candidate
Dept of Public and Social Administration
City University of Hong Kong
Home page: http://asrr.r-forge.r-project.org/rghuang.html




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