Christophe Rhodes <cs...@cantab.net> writes: > I have a dataset with a response variable and multiple factors with more > than two levels, which I have been fitting using lm() or glm(). In > these fits, I am generally more interested in deviations from the global > mean than I am in comparing to a "control" group, so I use contr.sum() > as the factor contrasts. I think I'm happy to interpret the > coefficients in the model summary as the effect of a particular factor > level on the deviation from the overall mean; I'm not after a highly > rigorous treatment of these coefficients and their standard errors, but > rather using them as suggestive of further things to investigate. > > [...] > > As far as I can tell, models m1 and m2 are semantically equivalent. Is > there a straightforward way of extracting the standard error and > t-statistic for the `redundant' comparison directly from m1? I'd rather > not have to fit two linear models if I can fit just one.
Did I post this to the wrong list? I'm still very much interested in any answer, or a redirection to a more appropriate forum... Thanks, Christophe ______________________________________________ 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.
