[R] nonparametric logistic regression based on locally weighted scatterplot smoothing (lowess)

[Thomas Lumley]

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 <tlumley at 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.berton at 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 <dwinsemius at 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 at 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 at 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