From: Bin Yue <leffgh_at_163.com>

Date: Mon, 10 Dec 2007 19:42:36 -0800 (PST)

Best regards,

Bin Yue

student for a Master program in South Botanical Garden , CAS

Date: Mon, 10 Dec 2007 19:42:36 -0800 (PST)

Dear list:

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.The columns are the levels of IV, and the rows are the levels of DV(0, or 1).For each column,we get the proprotions for DV=0 and DV=1 at given IV. Using the proportions the log odds can be computed.Is that right?

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?

In R , fitted(fit) gives the fitted probability for DV to be 1. Dose the observed probability exist ? If it does exist , how can I extract it ? If the IV is cartegorical , the DV can readily changed to be a tow-culumned matrix, thus log(the observed probabily/(1-the observed probability) might be the "log odds". I wonder what if the IV is continuous ?

Would you please help me ? Thank all very much again.
Regards,

Bin Yue

Best regards,

Bin Yue

student for a Master program in South Botanical Garden , CAS

-- View this message in context: http://www.nabble.com/the-observed-%22log-odds%22-in-logistic-regression-tp14267125p14267125.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help_at_r-project.org mailing list 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.Received on Tue 11 Dec 2007 - 03:49:48 GMT

Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Australia.

Archive generated by hypermail 2.2.0, at Tue 11 Dec 2007 - 08:30:18 GMT.

*
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help.
Please read the posting
guide before posting to the list.
*