Modeling zero-inflated count series with application to occupational health

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

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Original languageEnglish
Pages (from-to)47-52
Journal / PublicationComputer Methods and Programs in Biomedicine
Issue number1
Publication statusPublished - Apr 2004


A zero-inflated Poisson mixed autoregression model is presented for analyzing time series of count events with excess zeros. The model is motivated by the evaluation of a participatory ergonomics intervention intended to reduce manual handling workplace injuries over a specified time period. Random effects are introduced into the linear predictor of the model to account for serial correlation between successive observations. Parameter estimation is achieved by maximizing an appropriate log-likelihood function to obtain approximate residual maximum likelihood estimates. The method enables the evaluation of occupational intervention using population level aggregated count data series containing extra zeros. © 2003 Elsevier Ireland Ltd. All rights reserved.

Research Area(s)

  • Autocorrelation, Occupational health, Poisson regression, Random effects, Workplace injuries, Zero-inflation