R help - Mar 2020 - Posting: R-Project Code/Package for a Stepwise Multiple Regression Analysis

Statistics newbie over here getting her feet wet into the research realm.

I will be using the R-project to analyze the predictability of some data
using a stepwise multiple regression analysis. I would also like to have a
forced entry method option to avoid any methodology flaws, if possible,
too. Is there any existing R code or r-project add-on packages for this?

Details: 2 or more dependent variables, 5 or more independent variables.
These variables will be in the form of numbers such as age, height, etc.
There will be 2 steps. I am happy to provide any additional details for you
to better understand my situation as well.

Thank you in advance for your help! I'm open to any insights you have.

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Please search archives and Google. There are many resources. I think that
the MASS package has stepwise regression, but please confirm yourself.

On Mon, Mar 30, 2020, 09:45 Jastine bugayong <jbugayong1 at gmail.com>
wrote:
> Statistics newbie over here getting her feet wet into the research realm.
>
> I will be using the R-project to analyze the predictability of some data
> using a stepwise multiple regression analysis. I would also like to have a
> forced entry method option to avoid any methodology flaws, if possible,
> too. Is there any existing R code or r-project add-on packages for this?
>
> Details: 2 or more dependent variables, 5 or more independent variables.
> These variables will be in the form of numbers such as age, height, etc.
> There will be 2 steps. I am happy to provide any additional details for you
> to better understand my situation as well.
>
> Thank you in advance for your help! I'm open to any insights you have.
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
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Also see the 'rms' package.

If you use validate with bw=TRUE you can see often a given predictor will
be retained.

On Mon, Mar 30, 2020 at 11:57 AM stephen sefick <ssefick at gmail.com>
wrote:
> Please search archives and Google. There are many resources. I think that
> the MASS package has stepwise regression, but please confirm yourself.
>
> On Mon, Mar 30, 2020, 09:45 Jastine bugayong <jbugayong1 at
gmail.com> wrote:
>
> > Statistics newbie over here getting her feet wet into the research
realm.
> >
> > I will be using the R-project to analyze the predictability of some
data
> > using a stepwise multiple regression analysis. I would also like to
have
> a
> > forced entry method option to avoid any methodology flaws, if
possible,
> > too. Is there any existing R code or r-project add-on packages for
this?
> >
> > Details: 2 or more dependent variables, 5 or more independent
variables.
> > These variables will be in the form of numbers such as age, height,
etc.
> > There will be 2 steps. I am happy to provide any additional details
for
> you
> > to better understand my situation as well.
> >
> > Thank you in advance for your help! I'm open to any insights you
have.
> >
> >         [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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.
> >
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
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