Thanks Jose, but I doubt that the author of these analysis used such a "complex" approach.
Arnaud 2012/12/13 Jose Iparraguirre <jose.iparragui...@ageuk.org.uk> > Sorry, Arnaud, I misinterpreted the question.**** > > There isnt a built-in option in lm or glm to run pairwise deletion, but > in the psych package you can run regressions on covariance matrices > rather than on raw data. So, first, you can obtain a covariance matrix by > cov() with the option use="pairwise.complete.obs" or within psych, > set.cor( ,use="pairwise"), which will give you the correlations pairwise, > and then you use the function mat.regress using the pairwise matrix.**** > > Hope this helps,**** > > ** ** > > José **** > > ** ** > > ** ** > > *From:* Arnaud Mosnier [mailto:a.mosn...@gmail.com] > *Sent:* 13 December 2012 16:13 > *To:* Jose Iparraguirre > *Cc:* r-help@r-project.org > *Subject:* Re: [R] Pairwise deletion in a linear regression and in a GLM ? > **** > > ** ** > > 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**** > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > Wrap Up and Run 10k is back! > > Also, new for 2013 2km intergenerational walks at selected venues. 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Together they have formed the Age UK Group, dedicated to > improving the lives of people in later life. The three national Age > Concerns in Scotland, Northern Ireland and Wales have also merged with Help > the Aged in these nations to form three registered charities: Age Scotland, > Age NI, Age Cymru. > > ------------------------------ > [[alternative HTML version deleted]]
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