Russel-Research-Method-in-Anthropology

Multivariate Analysis 651
environments, residence appears to make no difference in wealth accumulation
among these informants.
Table 21.2, however, shows that after 5 years or more in the city, 68% (28/
41) were no longer poor by local standards. In fact, the odds of emerging from
TABLE 21.2
Wealth by Time in the City for Urban Migrants
Wealth 1 year 1–3 years 3–5 years 5 years Row totals
Not poor 6 10 12 28 56
Poor 77 60 44 13 194
Column totals 83 70 56 41 250
2 63.35, p .001
poverty increase steadily over time. There is no guarantee, of course, but the
Indians’ perception that urban migration works in their favor is substantially
correct from these data. Thus, controlling for time allows the significant bivariate
relation between wealth and urban residence to emerge.
While time is an important factor in understanding what’s going on, it
doesn’t tell us anything about how the process works. We know from many
studies that education is related positively to wealth. Table 21.3 shows the
TABLE 21.3
Wealth by Education for the Entire Sample
Wealth Did not complete 8th grade Completed 8th grade Row totals
Not poor 62 113 175
Poor 179 146 325
Column totals 241 259 500
2 17.59, p .001, OR 2.24
breakdown for the entire sample of 500, including the rural stay-at-homes and
the urban migrants. Chi-square is highly significant, and the odds ratio for this
table is OR2.24. The odds of being poor for those who haven’t completed
8 years of school are more than double those of people who have completed
the eighth grade.
Table 21.4 breaks down education by residence. Chi-square for this table is
also highly significant, and the odds ratio is 2.62. In other words, urbanites are
more than two-and-a-half times as likely to complete secundaria, or the eighth
grade. This, it appears, leads to greater wealth.
We can test this hypothesis by producing a single cross-tab of wealth by