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Distribution-free inference of zero-inflated binomial data for longitudinal studies

Author

Listed:
  • H. He
  • W. Wang
  • J. Hu
  • R. Gallop
  • P. Crits-Christoph
  • Y. Xia

Abstract

Count responses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated Poisson (ZIP) and zero-inflated negative binomial models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or ZIP distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling ZIB-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.

Suggested Citation

  • H. He & W. Wang & J. Hu & R. Gallop & P. Crits-Christoph & Y. Xia, 2015. "Distribution-free inference of zero-inflated binomial data for longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2203-2219, October.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:10:p:2203-2219
    DOI: 10.1080/02664763.2015.1023270
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    References listed on IDEAS

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