Boolean logit and probit in Stata
Bear F. Braumoeller
Harvard University
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Abstract. This paper introduces new statistical models, Boolean logit and probit, that
allow researchers to model binary outcomes as the results of Boolean inter-
actions among independent causal processes. Each process (or “causal
path”) is modeled as the unobserved outcome in a standard logit or
probit equation, and the dependent variable is modeled as the observed
product of their Boolean inter- action. Up to five causal paths can be
modeled, in any combination—A and B and C produce Y, A and (B or [C
and D]) produce Y, etc.
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Bear F. Braumoeller
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mlboolean, dichotomous dependent variable, Boolean, logit, probit, multiple causal paths, complexity, random utility
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