Hi Jose,

To my perception na.omit is different from a pairwise deletion.
With na.omit, you omit totally that case if there is a missing value for
one of the variable you consider in the model.
In the pairwise deletion, the case with some missing value is kept and
values that are not missing are used in the statistics calculations.

However, I agree that pairwise deletion is not good practice (so it would
be surprising that it is the default in lm !!).
I just when to be able to recalculate the statistics given in this thesis.

Arnaud




2012/12/13 Jose Iparraguirre <jose.iparragui...@ageuk.org.uk>

> Hi Arnaud,
>
> A quick help search of lm or glm tells you that 'the "factory-fresh"
> default is na.omit'.
> If you then look up 'na.omit', you'll read that it 'returns the object
> with incomplete cases removed'.
> So, pairwise deletion is the default option in both lm and glm.
>
> On a related note, it goes without saying that pairwise deletion is not
> good practice in most cases, and that R has ways to impute these missing
> cases depending on assumptions regarding the cause or nature of their
> missingness.
>
> Regards,
>
> José
>
>
> José Iparraguirre
> Chief Economist
> Age UK
>
>
>
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Arnaud Mosnier
> Sent: 13 December 2012 15:40
> To: r-help@r-project.org
> Subject: [R] Pairwise deletion in a linear regression and in a GLM ?
>
> Dear useRs,
>
> In a thesis, I found a mention of the use of pairwise deletion in linear
> regression and GLM (binomial family).
> The author said that he has used R to do the statistics, but I did not find
> the option allowing pairwise deletion in both lm and glm functions. Is
> there somewhere a package allowing that ?
>
> Thanks,
>
> Arnaud
>
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