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Boolean logit and probit in Stata

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  • Bear F. Braumoeller

    (Harvard University)

Abstract

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.

Suggested Citation

  • Bear F. Braumoeller, 2004. "Boolean logit and probit in Stata," Stata Journal, StataCorp LP, vol. 4(4), pages 436-441, December.
    • Handle: RePEc:tsj:stataj:v:4:y:2004:i:4:p:436-441
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    References listed on IDEAS

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    1. Braumoeller, Bear F., 2003. "Causal Complexity and the Study of Politics," Political Analysis, Cambridge University Press, vol. 11(3), pages 209-233, July.
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