Re: st: Relative Importance of predictors in regression

[Jorge Eduardo Pérez Pérez <jorge_perez@brown.edu>]

I should have been more specific, sorry, Ignore the SJ paper.

Analysis of variance with continuous covariates and regression are
general linear models. All these models are equivalent:

sysuse auto, clear
reg price mpg trunk
anova price c.mpg c.trunk
glm price mpg trunk, family(gaussian) link(identity)


The anova view of the model will yield the partial sums of squares
attributed to each regressor. In regression vocabulary, this would be
the model sum of squares of regressing the dependent variable on each
one of the independent variables, after partialling out the remaining
variables. For example, the MS attributed to mpg in the previous
regression could be obtained as follows, by first removing the
influence of trunk from both variables:

reg price trunk
predict lhs, resid
reg mpg trunk
predict rhs, resid
reg lhs rhs