Russel-Research-Method-in-Anthropology

616 Chapter 20
Environmentalists wouldn’t be so gung-ho if it were their jobs that were threatened.
1. Disagree 2. Neutral 3. Agree
Gery Ryan, Stephen Borgatti, and I used these items in a survey we ran
(Bernard et al. 1999), and table 20.10 shows the results. Notice that these
TABLE 20.10
Distribution of Responses on Two Ecological Attitude Items
Gung-ho
Force change
in lifestyle Disagree Neutral Agree Row totals
Disagree 16 7 61 84
Neutral 7 7 7 21
Agree 13 4 27 44
Column totals 36 18 95 149
items are reverse scored, so that a higher number indicates support for environmentalism.
If the two variables were perfectly related, then every respondent who
agreed with one statement would agree with the other; and every respondent
who disagreed with one statement would disagree with the other. Of course,
things never work out so neatly, but if you knew the proportion of matching
pairs among your respondents, you’d have a PRE measure of association for
ordinal variables. The measure would tell you how much more correctly you
could guess the rank of one ordinal variable for each respondent if you knew
the score for the other ordinal variable in a bivariate distribution.
What we would like is a PRE measure of association that tells us whether
knowing the ranking of pairs of people on one variable increases our ability
to predict their ranking on a second variable, and by how much. To do this,
we need to understand the ways in which pairs of ranks can be distributed.
This will not appear obvious at first, but bear with me.
The number of possible pairs of observations (on any given unit of analysis)
is
No. of pairs of observations n(n1)
2
Formula 20.12
where n is the sample size. There are (149)(148)/2 11,026 pairs of observations
in table 20.10.