Sorry, Arnaud, I misinterpreted the question. There isn't 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><mailto: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> [mailto: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<mailto: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<mailto: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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For the purposes of promoting Age UK Insurance, Age UK is an Appointed Representative of Age UK Enterprises Limited, Age UK is an Introducer Appointed Representative of JLT Benefit Solutions Limited and Simplyhealth Access for the purposes of introducing potential annuity and health cash plans customers respectively. Age UK Enterprises Limited, JLT Benefit Solutions Limited and Simplyhealth Access are all authorised and regulated by the Financial Services Authority. ------------------------------ This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are addressed. If you receive a message in error, please advise the sender and delete immediately. Except where this email is sent in the usual course of our business, any opinions expressed in this email are those of the author and do not necessarily reflect the opinions of Age UK or its subsidiaries and associated companies. Age UK monitors all e-mail transmissions passing through its network and may block or modify mails which are deemed to be unsuitable. Age Concern England (charity number 261794) and Help the Aged (charity number 272786) and their trading and other associated companies merged on 1st April 2009. 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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