R help - Jul 2009 - Logistic regression and R

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, 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?

Thank you very much!!! :-D

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Dear Carlos,

On Thu, Jul 30, 2009 at 6:11 PM, Carlos L?pez<natorro at 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/

and the following specific link on that page:

https://home.comcast.net/~lthompson221/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.
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