Skip to main content
padlock icon - secure page this page is secure

Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential?

Buy Article:

$52.00 + tax (Refund Policy)

Political scientists presenting binary dependent variable (BDV) models often hypothesize that variables interact to influence the probability of an event, Pr(Y). The current typical approach to testing such hypotheses is (1) estimate a logit or probit model with a product term, (2) test the hypothesis by determining whether the coefficient for this term is statistically significant, and (3) characterize the nature of any interaction detected by describing how the estimated effect of one variable on Pr(Y) varies with the value of another. This approach makes a statistically significant product term necessary to support the interaction hypothesis. We show that a statistically significant product term is neither necessary nor sufficient for variables to interact meaningfully in influencing Pr(Y). Indeed, even when a logit or probit model contains no product term, the effect of one variable on Pr(Y) may be strongly related to the value of another. We present a strategy for testing for interaction in a BDV model, including guidance on when to include a product term.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Document Type: Research Article

Affiliations: 1: Florida State University 2: University of North Texas 3: Emory University

Publication date: January 1, 2010

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more