Zero-inflated regression models for radiation-induced chromosome aberration data: A comparative study

María Oliveira, Jochen Einbeck, Manuel Higueras, Elizabeth Ainsbury, Pedro Puig, Kai Rothkamm

Research output: Contribution to journalArticleResearchpeer-review

22 Citations (Scopus)

Abstract

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Within the field of cytogenetic biodosimetry, Poisson regression is the classical approach for modeling the number of chromosome aberrations as a function of radiation dose. However, it is common to find data that exhibit overdispersion. In practice, the assumption of equidispersion may be violated due to unobserved heterogeneity in the cell population, which will render the variance of observed aberration counts larger than their mean, and/or the frequency of zero counts greater than expected for the Poisson distribution. This phenomenon is observable for both full- and partial-body exposure, but more pronounced for the latter. In this work, different methodologies for analyzing cytogenetic chromosomal aberrations datasets are compared, with special focus on zero-inflated Poisson and zero-inflated negative binomial models. A score test for testing for zero inflation in Poisson regression models under the identity link is also developed.
Original languageEnglish
Pages (from-to)259-279
JournalBiometrical Journal
Volume58
Issue number2
DOIs
Publication statusPublished - 1 Mar 2016

Keywords

  • Biological dosimetry
  • Chromosome aberrations
  • Count data
  • Overdispersion
  • Score tests
  • Zero inflation

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