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. Copyright 2004 by StataCorp LP.
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Article provided by StataCorp LP in its journal Stata Journal.
Volume (Year): 4 (2004) Issue (Month): 4 (December) Pages: 436-441 Download reference. The following formats are available: HTML
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Handle: RePEc:tsj:stataj:v:4:y:2004:i:4:p:436-441
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