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Computing interaction effects and standard errors in logit and probit models

Author

Listed:
  • Edward C. Norton

    (University of North Carolina at Chapel Hill)

  • Hua Wang

    (University of North Carolina at Chapel Hill)

  • Chunrong Ai

    (University of Florida)

Abstract

This paper explains why computing the marginal effect of a change in two variables is more complicated in nonlinear models than in linear models. The command inteff computes the correct marginal effect of a change in two interacted variables for a logit or probit model, as well as the correct standard errors. The inteff command graphs the interaction effect and saves the results to allow further investigation. Copyright 2004 by StataCorp LP.

Suggested Citation

  • Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
  • Handle: RePEc:tsj:stataj:v:4:y:2004:i:2:p:154-167
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    References listed on IDEAS

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    1. Thomas DeLeire, 2000. "The Wage and Employment Effects of the Americans with Disabilities Act," Journal of Human Resources, University of Wisconsin Press, vol. 35(4), pages 693-715.
    2. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
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