Hi, I have setup a simple logistic regression model with the glm() function, with the follow formula:
y ~ a + b where: 'a' is a continuous variable stratified by the levels of 'b' Looking over the manual for model specification, it seems that coefficients for unordered factors are given 'against' the first level of that factor. This makes for difficult interpretation when using factor 'b' as a stratifying model term. Setting up the model, minus the intercept term, gives me what appear to be more meaningful coefficients. However, I am not sure if I am interpreting the results from a linear model without an intercept term. Model predictions from both specifications (with and without an intercept term) are nearly identical (different by about 1E-16 in probability space). Are there any gotchas to look out for when removing the intercept term from such a model? Any guidance would be greatly appreciated. Cheers, -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341 ______________________________________________ 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.
