[R] weighted x variables with glm
I have a glm regression (quasi-poisson) of log(mu) on x but I have varying degrees of confidence in the x values, and can attach a numerical weighting to each. Can anyone help me with suggestions of how to analysise this. Is there an R package that would help? Wendy [[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.
Re: [R] weighted x variables with glm
Hi Wendy, In case you haven't see it, the glm function accepts an optional weights argument. Michael On 29 November 2010 09:42, Wendy Anderson newhorizonscand...@gmail.com wrote: I have a glm regression (quasi-poisson) of log(mu) on x but I have varying degrees of confidence in the x values, and can attach a numerical weighting to each. Can anyone help me with suggestions of how to analysise this. Is there an R package that would help? Wendy [[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. __ 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.
Re: [R] weighted x variables with glm
In case you haven't see it, the glm function accepts an optional weights argument. Thanks for the reply. But the philosopy behind weighting is the assumption of unequal variance in the y values. In normal regression one assumes that the x values are known without error Wendy Sorry Wendy - I posted my reply prior to engaging my brain (ie. didn't read your question properly). You're talking about Model II / major axis type methods. The smatr package might cater for what you're trying to do. Hope this helps (more). Michael __ 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.
Re: [R] weighted x variables with glm
Hello again Wendy, Actually, the simex package is probably a more useful suggestion... http://www.stat.uni-muenchen.de/~helmut/Texte/Simex_Rnews.pdf Michael On 29 November 2010 13:55, Michael Bedward michael.bedw...@gmail.com wrote: In case you haven't see it, the glm function accepts an optional weights argument. Thanks for the reply. But the philosopy behind weighting is the assumption of unequal variance in the y values. In normal regression one assumes that the x values are known without error Wendy Sorry Wendy - I posted my reply prior to engaging my brain (ie. didn't read your question properly). You're talking about Model II / major axis type methods. The smatr package might cater for what you're trying to do. Hope this helps (more). Michael __ 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.
