An alternative procedure for calculating the least-squares coefficient B1
is as follows:
1. Regress Y on X2
through Xk
, obtaining residuals EY/2
... k
.
2. Regress X1
on X2
through Xk
, obtaining residuals E1/2
... k
.
3. Regress the residuals EY/2 ... k
on the residuals E1/2 ... k
. The slope for this simple regression is the multiple-regression slope for X1, that is, B1.
(a) Apply this procedure to the multiple regression of prestige on education, income, and percentage of women in the Canadian occupational prestige data, confirming that the coefficient for education is properly recovered.
(b) The intercept for the simple regression in Step 3 is 0. Why is this the case?
(c) In light of this procedure, is it reasonable to describe B1
as the ‘‘effect of X1
on Y when the influence of X2; ...
; Xk
is removed from both X1
and Y’’?
(d) The procedure in this problem reduces the multiple regression to a series of simple regressions (in Step 3). Can you see any practical application for this procedure? (See the discussion of added-variable plots in Section 11.6.1.)