I am trying to make a little web interface for the lm() function. It calculates both anova F-tests and parameters and returns it in a nice table. However, I have a problem with matching the Anova predictors with the regression coefficients: For numeric predictors there is no problem: the coefficients have the same names as the predictors. However, when a factor IV is specified, lm() automatically converts this factor to dummy variables, which (of course) have different names than the orriginal predictor. The lm model that is returned contains a seperate parameter for every dummy variable.
Then when you use anova(lm.model) the function seems to know which of the parameters are dummies of one and the same factor, and takes these together in the anova-test. The anova() function returns the variance explained by the orriginal factor, which are all dummies. It does not show the seperate dummy variables anymore. Of course, this is exactly what you want in an analysis of variance. My question is: where in the lm or glm object is stored which of the parameters are dummies of the same factor? The only thing i could think of was using lm.model$xlevels, however manipulating these names in the lm-model did not confuse anova() at all, so I guess there is a better way. An additional question is if it is possible to specify the names of the dummy variables that lm/glm creates when a factor is specified as IV? -- View this message in context: http://www.nabble.com/matching-predictors-and-dummies-tp18405023p18405023.html Sent from the R devel mailing list archive at Nabble.com. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel