Hi Dylan, >> While this topic is fresh, are there any compelling reasons to use Model >> II >> regression?
The fact that it is the type of regression used in principal component analysis makes it a compelling method. Compelling reason? It is used to take account of measurement errors in both y _and_ x. Usually practioners/analysts would sidestep this by putting what is measured with least error on the x-axis and regress y on that. For instance, in doing calibration curves in nutrient analysis where the analyte is measured using a spec. Then the spec reading goes on x. I can't tell you how often I have seen analysts put the (usually) inaccurately determined analyte on x and the spec reading on y. HTH, Mark. Dylan Beaudette-2 wrote: > > On Friday 29 August 2008, Mark Difford wrote: >> Hi Danilo, >> >> >> I need to do a model II linear regression, but I could not find out >> >> how!! >> >> The smatr package does so-called model II (major axis) regression. >> >> Regards, Mark. > > While this topic is fresh, are there any compelling reasons to use Model > II > regression? > > Cheers, > > Dylan > > -- > Dylan Beaudette > Soil Resource Laboratory > http://casoilresource.lawr.ucdavis.edu/ > University of California at Davis > 530.754.7341 > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/model-II-regression---how-do-I-do-it--tp19224427p19226644.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
