Modelling bivariate count series with excess zeros

Lee, Andy H., Wang, Kui, Yau, Kelvin K. W., Carrivick, Philip J. W. and Stevenson, Mark R. (2005) Modelling bivariate count series with excess zeros. Mathematical Biosciences, 196 2: 226-237. doi:10.1016/j.mbs.2005.05.001

Author Lee, Andy H.
Wang, Kui
Yau, Kelvin K. W.
Carrivick, Philip J. W.
Stevenson, Mark R.
Title Modelling bivariate count series with excess zeros
Journal name Mathematical Biosciences   Check publisher's open access policy
ISSN 0025-5564
Publication date 2005-08
Sub-type Article (original research)
DOI 10.1016/j.mbs.2005.05.001
Volume 196
Issue 2
Start page 226
End page 237
Total pages 12
Place of publication Philadelphia, PA, U.S.A.
Publisher Elsevier
Language eng
Subject 010202 Biological Mathematics
Abstract Bivariate time series of counts with excess zeros relative to the Poisson process are common in many bioscience applications. Failure to account for the extra zeros in the analysis may result in biased parameter estimates and misleading inferences. A class of bivariate zero-inflated Poisson autoregression models is presented to accommodate the zero-inflation and the inherent serial dependency between successive observations. An autoregressive correlation structure is assumed in the random component of the compound regression model. Parameter estimation is achieved via an EM algorithm, by maximizing an appropriate log-likelihood function to obtain residual maximum likelihood estimates. The proposed method is applied to analyze a bivariate series from an occupational health study, in which the zero-inflated injury count events are classified as either musculoskeletal or non-musculoskeletal in nature. The approach enables the evaluation of the effectiveness of a participatory ergonomics intervention at the population level, in terms of reducing the overall incidence of lost-time injury and a simultaneous decline in the two mean injury rates.
Keyword Autoregression
Bivariate Poisson
EM algorithm
Random effects
Zero-inflated Poisson model
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
ERA 2012 Admin Only
School of Chemistry and Molecular Biosciences
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Citation counts: TR Web of Science Citation Count  Cited 10 times in Thomson Reuters Web of Science Article | Citations
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