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Condition 3: Precedence, or Time Order

Besides a nonspurious association, something else is required to establish a cause- and-effect relation between two variables: a logical time order. Firefighters don’t cause fires—they show up after the blaze starts. African Americans have higher blood pressure, on average, than Whites do, but high blood pressure does not cause people to be African American.

Unfortunately, things are not always clear-cut. Does adoption of new technologies cause wealth, or is it the other way around? Does urban migration cause dissatisfaction with rural life, or the reverse? Does consumer demand cause new products to appear, or vice versa? Does the growth in the number of lawsuits cause more people to study law so that they can cash in, or does overproduction of lawyers cause more lawsuits?

What about the increase in elective surgery in the United States? Does the increased supply of surgeons cause an increase in elective surgery, or does the demand for surgery create a surfeit of surgeons? Or are both caused by external variables, like an increase in discretionary income in the upper middle class or the fact that insurance companies pay more and more of Americans’ medical bills?

Figure 2.4 shows three kinds of time order between two variables. Read figure 2.4a as ‘‘a is antecedent to b.’’ Read figure 2.4b as ‘‘a and b are antecedent to c.’’ And read figure 2.4c as “a is antecedent to b, which is an intervening variable antecedent to c.’’ A lot of data analysis is about understanding and controlling for antecedent and intervening variables—about which much more in chapter 21.

FIGURE 2.4.

Time order between two or three variables.

 
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