the observed "log odds" in logistic regression

Bin Yue <leffgh <at> 163.com> writes:

     After reading the following two links:
http://luna.cas.usf.edu/~mbrannic/files/regression/Logistic.html
http://www.tufts.edu/~gdallal/logistic.htm
     I've known the mathematical basis for logistic regression.However I
am
still not so sure about the "logit "
     For a categorical independent variable, It is  easy to understand
the
procedures  how "log odds" are calculated. As I know, First the
observations
are grouped according to the IV and DV, generating a contingency table.

..

   My problem  is this : in my data set , the IVs are continuous
variables,
do I still have to generate such a table and compute the log odds for
each
level of IV according to which the log odds are calculated?  

Let's assume you are going to use glm in package stats. glm can be fed
with 
data in three ways; in your case, you should use the "one-row/one 0-1
event"
format, that is the "long" style. You do not have to compute any logit, 
glm will do that for your.

The example coming closest to your's is the birthwt example in 
MASS/scripts/ch07.R  and chapter 7 in Venables/Ripley MASS. Try to
generate 
a small, self-running example with a data set similar to your's, and you
have 
a good chance to get a more detailed answer.

Dieter