This paper introduces new statistical models, Boolean logit and probit, that allow researchers to model binary outcomes as the results of Boolean interactions 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 interaction. 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.
BraumoellerB. F.2003. Causal complexity and the study of politics. Political Analysis11(3): 209–233.
2.
CBS News.1998. CBS News Monthly Poll #1, February 1998 [Computer file]. ICPSR version.New York: CBS News [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor].
3.
RaginC. C.1987. The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies.Berkeley: University of California Press.
