Hi there,



I take advantage of this chat to ask other question related to logistic
regression. This is my first time as well.

I have data that I want to model but I’m not sure if glm() is the correct
function to use. My problem is as follow, I used Oxford Instability Score of
the shoulder (OIS, independent variable) as indicative of the outcome (
12-20 best, to 41-60 worst outcome, 5 possible results). Looking for many
independent variables like categorical and numerical I want to see their
prognostic impact on the outcome.

There is a function which I can use to model my problem? I heard about
multinomial logistic regression but I did not able to find nothing related
to it.



Any help would be much appreciated.


Marlene.

2009/7/31 G. Jay Kerns <gkerns@ysu.edu>

> Dear Carlos,
>
> On Thu, Jul 30, 2009 at 6:11 PM, Carlos López<natorro@fisica.unam.mx>
> wrote:
> > Hello everybody :-)
> >
> > I have some data that I want to model with a logistic regression, most of
> > the independent variables are numeric and the only dependent is
> categorical,
> > I was thinking that I could apply a logistic regression using glm but I
> > wanted to deepen my knowledge of this so I tried to do some reading and
> > found the "iris" dataset, now I would like to ask two things, first if
> you
> > know of any bibliography to read more about the logistic regression and R
> so
> > I could understand and interpret better the output,
>
>
> See the following
>
> https://home.comcast.net/~lthompson221/<https://home.comcast.net/%7Elthompson221/>
>
> and the following specific link on that page:
>
> https://home.comcast.net/~lthompson221/Splusdiscrete2.pdf<https://home.comcast.net/%7Elthompson221/Splusdiscrete2.pdf>
>
> which is a manual to accompany Agresti's _Categorical Data Analysis_.
> In particular, you may want to check out Chapter 5 (and also some of
> 4).
>
>
> >and second, what could I
> > do when I have some independent variables that are not only numerical but
> > categorical too, i.e. mixed (categorical and numerical), can I still use
> a
> > logistic regression?
>
> Easy peasy, lemon squeezy.  See page 78.
>
> Hope this helps,
> Jay
>
>
>
>
>
>
>
>
>
>
>
>
> ***************************************************
> G. Jay Kerns, Ph.D.
> Associate Professor
> Department of Mathematics & Statistics
> Youngstown State University
> Youngstown, OH 44555-0002 USA
> Office: 1035 Cushwa Hall
> Phone: (330) 941-3310 Office (voice mail)
> -3302 Department
> -3170 FAX
> VoIP: gjkerns@ekiga.net
> E-mail: gkerns@ysu.edu
> http://www.cc.ysu.edu/~gjkerns/ <http://www.cc.ysu.edu/%7Egjkerns/>
>
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