this works). Applied to a linear-model object, summary() produces coefficients, etc. (as mentioned), while anova() produces a (sequential) ANOVA table. This seems apparent to me from the output.
What I'm having trouble with is understanding the difference between aov() and lm() [since it seems like if I do a summary() after fitting using aov(), the output is the same as doing anova() after an lm()]. Now, the outputs from aov() and lm() are different - the siginificant effects are different. I think this may have to do with how these functions treat the data - i.e. whether the function considers the data as being in coded or uncoded units. Is this correct? From what I could tell, aov() will code the data automatically and then present the ANOVA table whereas lm() does not code the data. This pretty much explains everything so far..
There's one problem though - how do I get the coefficients that are calculated from the data after they are coded by aov()? The problem here is that my factor levels are 0 and 1 instead of the usual -1 and 1... if I run coefficients() after a aov() fit or an lm() fit, I get the same coefficients... these coeffs. don't seem right (I compared with the coefficients from Minitab and JMP -both give coefficients after coding the data into a -1, 1 form).. I could of course modify my data and change all the 0 levels to -1 but is there a way in R to get coefficients that correspond to coded data?
More generally, it probably makes sense to read introductory material about R -- such as the introductory manual that comes with the software
Yes, I have read some of these (and maybe I should read more :-))... thanks for the pointer.. on the same note, is there any reference that talks about how lm() and aov() treat data - coded vs. uncoded etc...
Thanks a lot for the help.. it is greatly appreciated! nirmal
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