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A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives

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  • Martin Ridout
  • John Hinde
  • Clarice G. B. Demétrio

Abstract

Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution. We therefore provide a score test for testing zero‐inflated Poisson regression models against zero‐inflated negative binomial alternatives.

Suggested Citation

  • Martin Ridout & John Hinde & Clarice G. B. Demétrio, 2001. "A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives," Biometrics, The International Biometric Society, vol. 57(1), pages 219-223, March.
    • Handle: RePEc:bla:biomet:v:57:y:2001:i:1:p:219-223
    DOI: 10.1111/j.0006-341X.2001.00219.x
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    1. Gupta, Pushpa L. & Gupta, Ramesh C. & Tripathi, Ram C., 1996. "Analysis of zero-adjusted count data," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 207-218, December.
    2. N. E. Breslow, 1984. "Extra‐Poisson Variation in Log‐Linear Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(1), pages 38-44, March.
    3. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    4. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-238, July-Sept.
    5. Gurmu, Shiferaw, 1991. "Tests for Detecting Overdispersion in the Positive Poisson Regression Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 215-222, April.
    6. Saha, Atanu & Dong, Diangsheng, 1997. "Estimating Nested Count Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(3), pages 423-430, August.
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