Hi! Thanks for the link. I've already stumbled upon that explanation. I'm able to understand how the coding schemes are applied in the supplied examples, but they only use a single explanatory variable. My problem is with understanding the model when there are multiple categorical explanatory variables.
-- Joao. On Fri, Jul 27, 2012 at 1:04 PM, Jean V Adams <jvad...@usgs.gov> wrote: > Joao, > > There's a very thorough explanation at > http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm > > Jean > > > Joao Azevedo <joao.c.azev...@gmail.com> wrote on 07/27/2012 06:32:31 AM: > >> >> Hi! >> >> I'm failing to understand the value of the intercept value in a >> multiple linear regression with categorical values. Taking the >> "warpbreaks" data set as an example, when I do: >> >> > lm(breaks ~ wool, data=warpbreaks) >> >> Call: >> lm(formula = breaks ~ wool, data = warpbreaks) >> >> Coefficients: >> (Intercept) woolB >> 31.037 -5.778 >> >> I'm able to understand that the value of intercept is the mean value >> of breaks when wool equals "A", and that adding up the "woolB" >> coefficient to the intercept value I get the mean value of breaks when >> wool equals "B". However, if I also consider the tension variable in >> the model, I'm unable to figure out the meaning of the intercept >> value: >> >> > lm(breaks ~ wool + tension, data=warpbreaks) >> >> Call: >> lm(formula = breaks ~ wool + tension, data = warpbreaks) >> >> Coefficients: >> (Intercept) woolB tensionM tensionH >> 39.278 -5.778 -10.000 -14.722 >> >> I thought it would be the mean value of breaks when either wool equals >> "A" or tension equals "L", but that isn't true for this dataset. >> >> Any clues on interpreting the value of intercept? >> >> Thanks! >> >> -- >> Joao. ______________________________________________ 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.
