Russel-Research-Method-in-Anthropology

326 Chapter 12
12 societies and 11 traits. Carneiro, you’ll recall, coded 100 societies for 354
traits and then went looking for subsets of the data that showed the desired
pattern. When he did this in the 1960s, it was heroic work. Today, Anthropac
(Borgatti 1992a, 1992b) has a routine for looking at big matrices of pluses and
minuses, rearranging the entries into the best pattern, calculating the CR, and
showing you which units of analysis and traits to drop in order to find the
optimal solution to the problem.
Data Scale, Variables Don’t
DeWalt (1979) used Guttman scaling to test his index of material style of
life in a Mexican farming community. He scored 54 informants on whether
they possessed eight material items (a radio, a stove, a sewing machine, etc.)
and achieved a remarkable CR of .95. This means that, for his data, the index
of material style of life is highly reliable and differentiates among informants.
Remember: Only data scale, not variables. If the items in a cumulative
index form a Guttman scale with 0.90 CR or better, we can say that, for the
sample we’ve tested, the concept measured by the index is unidimensional.
That is, the items are a composite measure of one and only one underlying
concept. DeWalt’s data show that, for the informants he studied, the concept
of ‘‘material style of life’’ is unidimensional—at least for the indicators he
used.
The Guttman technique tests whether unidimensionality holds for a particular
set of data. An index must be checked for its Guttman scalability each time
it is used on a population. My hunch is that DeWalt’s material-style-of-life
scale has its analog in nearly all societies. The particular list of items that
DeWalt used in rural Mexico may not scale in a middle-class neighborhood of
Ulan Bator, but some list of material items will scale there. You just have to
find them.
The way to do this is to code every household in your study for the presence
or absence of a list of material items. The particular list could emerge from
participant observation or from informal interviews. Then you’d use Anthropac
to sort out the matrix, drop some material items, and build the material
index that has a CR of 0.90 or better. Greg Guest (2000) did this in his study
of 203 households in an Ecuadorian fishing village. He gave each household
a score from 1 to 7, depending how many material items they had. That score
correlated significantly with the education level of the head of each household.
(We’ll get to correlation and statistical significance in chapter 20.) Since we
expect a correlation between wealth and education, this adds construct validity
to Guest’s scale.
Careful, though. Oliver Kortendick tried to develop a Guttman scale of