Analysis of zero-inflated poisson data incorporating extent of exposure

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)963-975
Journal / PublicationBiometrical Journal
Volume43
Issue number8
Publication statusPublished - 2001

Abstract

When analyzing Poisson count data sometimes a high frequency of extra zeros is observed. The Zero-Inflated Poisson (ZIP) model is a popular approach to handle zero-inflation. In this paper we generalize the ZIP model and its regression counterpart to accommodate the extent of individual exposure. Empirical evidence drawn from an occupational injury data set confirms that the incorporation of exposure information can exert a substantial impact on the model fit. Tests for zero-inflation are also considered. Their finite sample properties are examined in a Monte Carlo study.

Research Area(s)

  • Count data, Em algorithm, Exposure, Poisson regression, Zero-inflation