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Infinite Parameter Estimates in Logistic Regression: Opportunities, Not Problems

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  • David Rindskopf

Abstract

Infinite parameter estimates in logistic regression are commonly thought of as a problem. This article shows that in principle an analyst should be happy to have an infinite slope in logistic regression, because it indicates that a predictor is perfect. Using simple approaches, hypothesis tests may be performed and confidence intervals calculated even when a slope is infinite. Some functions of parameters that are infinite are still well defined, and reasonable estimates of these quantities (in particular, LD50) may be obtained even when the maximum likelihood estimates do not, in a strict sense, exist. Surprisingly, these techniques can provide more reasonable and useful results than the most popular alternative method, exact logistic regression.

Suggested Citation

  • David Rindskopf, 2002. "Infinite Parameter Estimates in Logistic Regression: Opportunities, Not Problems," Journal of Educational and Behavioral Statistics, , vol. 27(2), pages 147-161, June.
    • Handle: RePEc:sae:jedbes:v:27:y:2002:i:2:p:147-161
    DOI: 10.3102/10769986027002147
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