Russel-Research-Method-in-Anthropology

Multivariate Analysis 667
In fact, INCOME explains 43.82% of the variance in motor vehicle deaths
(r .662 and r 2 is .4382) and VIOLRATE explains 6% of the variance in
motor vehicle deaths (r .245 and r 2 is .0600). Together, though, INCOME
and VIOLRATE have a multiple-R of .762 and an R 2 of .581. Here again, the
two variables explain more variance working together than they explain working
separately.
In other words, it’s the complex association of per capita income and the
level of violence that explains so much variance in both the rate of teenage
births and the rate of motor vehicle deaths. It turns out that lots of things are
best explained by a series of variables acting together.
Caution: Automated Regression Now Available Everywhere
All of the major programs for statistical analysis today produce what is
called a stepwise multiple regression. You specify a dependent variable and
a series of independent variables that you suspect play some part in determining
the scores of the dependent variable.
The program looks for the independent variable that correlates best with the
dependent variable and then adds in the variables one at a time, accounting for
more and more variance, until all the specified variables are analyzed, or until
variables fail to enter because incremental explained variance is lower than a
preset value, say, 1%. (There are even programs that test all possible path analysis
equations . . . more on path analysis in a bit.)
Stepwise multiple regression is another one of those controversial hot topics
in data analysis. Some people feel strongly that it is mindless and keeps you
from making your own decisions about what causes what in a complex set
of variables. It’s rather like the significance test controversy and the shotgun
controversy I discussed in chapter 20.
My take on it is the same: Learn to use all the tools and make your own
decisions about the meaning of your findings. It’s your responsibility to do the
data processing and it’s your responsibility to determine the meaning of your
findings. Don’t let robots take over any of your responsibilities. And don’t be
afraid to use all the hot new tools, either.
Examples of Multiple Regression
Graves and Lave (1972) modeled the starting wage of Navajo men who
moved from the reservation in the 1960s to Denver. Graves and Lave started
with 19 variables that they thought might relate in some way to starting
wage—things like age, marital status, father’s occupation, proficiency in