Actually they say they used SAS, and Googling for "SAS local linear logistic" suggests they used PROC GAM with the LOESS() smoother. Probably quite similar to gam::gam().
-thomas On Sun, Jun 5, 2011 at 9:12 AM, Thomas Lumley <tlum...@uw.edu> wrote: > The Stanform gam() [gam package] has choices of spline or > local-polynomial (defaulting to local-linear) smoothers. That's > probably the best match for the description. It shouldn't be > necessary to guess -- the paper should have cited the package -- but > we know that is often missed. > > -thomas > > On Sun, Jun 5, 2011 at 7:43 AM, Bert Gunter <gunter.ber...@gene.com> wrote: >> Take a look at packages mgcv or gam (and probably others). Different >> smoothers are used, but it's nonlinear, nonparametric logistic >> regression. which is usually the important part. It also penalizes, >> which can be even more important than which smoother is used. >> >> -- Bert >> >> On Sat, Jun 4, 2011 at 9:02 AM, David Winsemius <dwinsem...@comcast.net> >> wrote: >>> >>> On Jun 4, 2011, at 11:41 AM, zhu yao wrote: >>> >>>> Dear UseRs: >>>> >>>> Recently, I have read an article regarding the association between age and >>>> lymph node metastases. >>>> http://jco.ascopubs.org/content/27/18/2931.long >>>> In statistical analysis, the authors stated "Because a nonlinear >>>> relationship between age and lymph node involvement was expected based on >>>> existing literature, lymph node involvement was also regressed on age >>>> using >>>> nonparametric logistic regression based on locally weighted scatterplot >>>> smoothing (lowess)." >>>> <http://jco.ascopubs.org/content/27/18/2931.long#ref-11> >>>> Could someone explain nonparametric logistic regression based on locally >>>> weighted scatterplot smoothing (lowess)? >>>> Or it is nonparametric regression based on locally weighted scatterplot >>>> smoothing (lowess) >>>> >>> >>> One can use a logistic link and a local likelihood. Loader describes the >>> advantages of such a strategy and shows a worked example in pages 60-65 of >>> her text "Local Regression and Likelihood". But there is no apparent R >>> content in this question (and the authors of the above paper said they used >>> SAS) so this very much off-topic for this list. You really should start such >>> requests for explication by addressing the authors of the paper. Two other >>> web-based statistical sites for general or medical statistics questions can >>> be found at the GoogleGroups MedStats group and >>> http://stats.stackexchange.com/ . >>> >>> -- >>> David Winsemius, MD >>> West Hartford, CT >>> >>> ______________________________________________ >>> 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. >>> >> >> >> >> -- >> "Men by nature long to get on to the ultimate truths, and will often >> be impatient with elementary studies or fight shy of them. If it were >> possible to reach the ultimate truths without the elementary studies >> usually prefixed to them, these would not be preparatory studies but >> superfluous diversions." >> >> -- Maimonides (1135-1204) >> >> Bert Gunter >> Genentech Nonclinical Biostatistics >> >> ______________________________________________ >> 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. >> > > > > -- > Thomas Lumley > Professor of Biostatistics > University of Auckland > -- Thomas Lumley Professor of Biostatistics University of Auckland ______________________________________________ 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.
