On Mon, 2007-12-10 at 19:42 -0800, Bin Yue wrote: (...) > 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?
If IV is a continuous variable isn't possible you create a contingency table because don't exist levels. Similar is not possible calculate de log odds of P(IV=x) but is possible calculate log odds of P(IV<x) or log odds of P(IV=x+delta) with delta tend to zero. In this case is common create a cut-off for IV and fit log odds of P(IV>x) > 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 ? > And about the residuals. It seems that the residual is not the actual > DV minus the fitted probability. For in my model extreme residuals lie well > beyond (0,1). I wonder how the residual is computed. > Would you please help me ? Thank all very much again. So to help you send a small part of your data and a reproductive example to us because is more easy understand your question this way -- Bernardo Rangel Tura, M.D,MPH,Ph.D National Institute of Cardiology Brazil ______________________________________________ R-help@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.