[Resending -- recipient list length issue] "John Sorkin" <[EMAIL PROTECTED]> writes:
> Peter Erm, that was Paul's question, not mine! If you want to help, please look at the pattern of residuals which he put up on the web on my request.... > You question is difficult to answer without more information about the > distribution of your residuals. Different residual patterns call for > different transformations to stabilize the variance. One very common > form of heterocedasticity is increasing variance with increasing values > of an independent predictor, i.e. the variance of the residuals of y=x > increase as x increases. In this case a log transformation of some, or > all, of the independent variables of the helps. Please also note the > comment by Bert Gunter (included below) in which some important points > are raised, particularly about extreme values. > > If you want more help, please describe the pattern of your residuals. > > > John Sorkin M.D., Ph.D. > Chief, Biostatistics and Informatics > Baltimore VA Medical Center GRECC, > University of Maryland School of Medicine Claude D. Pepper OAIC, > University of Maryland Clinical Nutrition Research Unit, and > Baltimore VA Center Stroke of Excellence > > University of Maryland School of Medicine > Division of Gerontology > Baltimore VA Medical Center > 10 North Greene Street > GRECC (BT/18/GR) > Baltimore, MD 21201-1524 > > (Phone) 410-605-7119 > (Fax) 410-605-7913 (Please call phone number above prior to faxing) > [EMAIL PROTECTED] > > >>> Berton Gunter <[EMAIL PROTECTED]> 8/3/2006 11:56:28 AM >>> > I know I'm coming late to this, but ... > > > > Is someone able to suggest to me a transformation to overcome the > > > problem of heterocedasticity? > > It is not usually useful to worry about this. In my experience, the > gain in > efficiency from using an essentially ideal weighted analysis vs. an > approximate unweighted one is usually small and unimportant > (transformation > to simplify a model is another issue ...). Of far greater importance > usually > is the loss in efficiency due to the presence of a few "unusual" > extreme > values; have you carefully checked to make sure that none of the large > sample variances you have are due merely to the presence of a small > number > of highly discrepant values? > > > -- Bert Gunter > Genentech Non-Clinical Statistics > South San Francisco, CA > > "The business of the statistician is to catalyze the scientific > learning > process." - George E. P. Box > > ______________________________________________ > [email protected] 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. > -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [email protected] 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.
