Hi Robert, In R, the default treatment contrasts for factor class variables in regression treats the first level as the reference group when creating the contrast matrix for the regression, so it is not really a matter of changing the formula.
This might provide some insight: http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm There are many ways to handle categorical data, and without knowing exactly what you want, it is difficult to give any sound suggestions. It really depends on your question. Cheers, Josh On Thu, Oct 14, 2010 at 12:34 PM, Robert Quinn <rqu...@fbr.org> wrote: > I have the following formula for a linear model: > > z <- lm(y~x + factor(a) + factor(b), data=NT2010) > > where a (groups) and b (Sub-groups) are categorical variables (factors), x > is a continuous covariate, and y the response variable. Since b is nested > within a, the formula can also be written as: > > z <- lm(y~x + factor(a) + factor(a)/factor(b), data=NT2010) > > and the same output is achieved when summary(z) is called. > > How can I get the output to show all 3 groups that I have inputted? There > are only group 2 and group 3 on the output, group 1 is missing. Also there > is a subgroup (subgroup 1) of the total 9 subgroups missing. I would like > to see the p-value of the missing group and missing sub-group even though > I'm sure they are not significantly different (>0.05). How do I change the > original formula to get all groups and sub-groups outputted? > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. -- Joshua Wiley Ph.D. Student, Health Psychology University of California, Los Angeles http://www.joshuawiley.com/ ______________________________________________ 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.
