[Solution]Complex Configura! Rules

Besides their cognitive ease and prior suggestion, complex configura! rules are easy to learn because it is easy to weave a causal narrative around a…

Besides their cognitive ease and prior suggestion, complex configura! rules are easy to learn because it is easy to weave a causal narrative around a configura! theory. These coherent narratives cement a dependence between variables that is easy to express but may overweight these “causal” cues, at the cost of ignoring others. Linear combinations yield no such coherence. Meehl provides the following example from clinicial psychology, describing the case of a woman who was ambivalent toward her husband. One night the woman came home from a movie alone. Then:
Entering the bedroom, she was terrified to see, for a fraction of a second, a large black bird (“a raven, I guess”) perched on her pillow next to her husband’s head. . . . She recalls “vaguely, some poem we read in high school.”
Meehl hypothesized that the woman’s vision was a fantasy, based on the poem “The Raven” by Edgar Allen Poe: “The [woman’s] fantasy is that like Poe’s Lenore, she will die or at least go away and leave him [the husbandl alone.” Meehl was using a configura! rule that gave more weight to the raven vision because the woman knew the Poe poem. A linear rule, simply weighting the dummy variables “raven” and “knowledge of Poe,” yields a narrative that is much clumsier than Meehl’s compelling analysis. Yet such a model might well pay attention to other factors, such as the woman’s age, education, and so forth, which might also help explain her ambivalence.
Configura[ rules can emerge naturally from trying to explain past cases. People learn by trying to fit increasingly sophisticated general rules to previous cases. Complicated configura! rules offer plenty of explanatory flexibility. For example, a 6-variable model permits 15 two-way interactions, and a 10-variable model allows 45 interactions. 13 In sports, for instance, statistics are so plentiful and refined that it is easy to construct subtle “configuralities” when global rules fail. Bucky Dent was an average New York Yankee infielder, except in the World Series, where he played “above his head,” hitting much better than predicted by his overall average. (The vari- able “Dent” was not highly predictive of success, but adding the interaction “Dent” x “Series” was.) 14 Because people are reluctant to accept the possibility of random error (Einhorn, 1986), increasingly complicated configura! ex- planations are born.

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