Applying glm coefficients (Beginner Question)
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