On Sep 20, 2012, at 6:55 AM, SirRon wrote: > Hello, > I am working with a dataset with three variables and one binomial parameter. > The glm function provides coefficients for these three variables, e.g. > -1.5 | 27.2 | -2.9 > > If I'm not mistaken, $fitted.values gives me an estimate of how likely my > parameter is to be true/1 .
Not at all how I would have expressed it. > I would like to apply these coefficients on > other variables to predict the binomial parameter but I'm not sure how to > make use of them. On other instances of similarly measured variables? Then use the new data argument to predict(). > > To clarify a bit more I'm looking for a formula to calculate the chance that > the parameter is true/1, based on the three variables/coefficients, > something like > > -1.5*V1+27.2*V2-2.9*V2 I am guessing you will be using the type="response" argument to predict(), but again is is not the case that this will be answer the question as you have expressed it and I have interpreted it. It is not going to return the probability that the "parameter is true", at least if the word "parameter" is what most people are calling "coefficient". ?predict.glm > I hope someone understands my awkwardly worded question and is able to help > me out - thanks! Awkwardly worded questions will get much better answers if they are accompanied by some test data. -- David Winsemius, MD Alameda, CA, USA ______________________________________________ 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.
