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Modeling underdispersed count data with generalized Poisson regression

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Listed:
  • Tammy Harris

    (University of South Carolina)

  • Zhao Yang

    (Quintiles, Inc.)

  • James W. Hardin

    (University of South Carolina)

Abstract

We present motivation and new Stata commands for modeling count data. While the focus of this article is on modeling data with underdispersion, the new command for fitting generalized Poisson regression models is also suitable as an alternative to negative binomial regression for overdispersed data.

Suggested Citation

  • Tammy Harris & Zhao Yang & James W. Hardin, 2012. "Modeling underdispersed count data with generalized Poisson regression," Stata Journal, StataCorp LLC, vol. 12(4), pages 736-747, December.
    • Handle: RePEc:tsj:stataj:v:12:y:2012:i:4:p:736-747
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    References listed on IDEAS

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    1. H. J. H. Tuenter, 2000. "On the generalized Poisson distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 54(3), pages 374-376, November.
    2. Weiren Wang & Felix Famoye, 1997. "Modeling household fertility decisions with generalized Poisson regression," Journal of Population Economics, Springer;European Society for Population Economics, vol. 10(3), pages 273-283.
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    15. Lin, Siyuan & Argys, Laura M. & Averett, Susan L., 2023. "Exposure to the One-Child Policy and Fertility among Chinese Immigrants to the US," IZA Discussion Papers 16329, IZA Network @ LISER.
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    18. Vimefall, Elin, 2015. "Income diversification among female-headed farming households," Working Papers 2015:11, Örebro University, School of Business.
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