Looking forward to it ...

KIM
Malaysia

On Wed, Oct 3, 2018 at 10:32 AM Jeff Laux <jeffl...@gmail.com> wrote:

> Although no code is given, it can be inferred from this:
>       https://stats.stackexchange.com/a/179945/
> Best, Jeff
>
>
> On 10/2/2018 11:54 AM, R. Mark Sharp wrote:
> > I am developing a short presentation for people with applied statistical
> backgrounds who have used backward stepwise variable selection where they
> remove variables based on small coefficient values, coefficient P values >
> 0.05, and large variances.
> >
> > I am wanting to provide some demonstration code in R that highlights
> some of the weakness as described by Frank Harrell (citation below).
> >
> > Of particular interest are (1) failure to include informative predictor
> variables (categorical and continuous) and (2) lowered standard errors for
> the coefficients in the final model. I have code to demonstrate inclusion
> of too many false predictors.
> >
> > I expect this code is available, but I have not found it. Guidance would
> be appreciated.
> >
> > Mark
> > P.S. I have started a public github package at
> https://github.com/rmsharp/stepwiser
> > I has very little in it thus far.
> >
> >
> > Frank E. Harrell. Regression Modeling Strategies with applications to
> linear models, logistic regression, and survival analysis, Springer Series
> in Statistics. Springer-Verlag. 2015.
> >
> >
> > R. Mark Sharp, Ph.D.
> > Data Scientist and Biomedical Statistical Consultant
> > 7526 Meadow Green St.
> > San Antonio, TX 78251
> > mobile: 210-218-2868
> > rmsh...@me.com
> >
> > _______________________________________________
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> > https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
> >
> > ---
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> >
> >
>
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