Modelling bivariate count series with excess zeros
MetadataShow full item record
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.
Lee, Andy and Wang, Kui and Carrivick, Philip and Yau, Kelvin K.W. and Stevenson, Mark. R. (2005) Modelling bivariate count series with excess zeros, Mathematical Biosciences 196:226-237.
The link to this article is:
Copyright 2005 Elsevier B.V. All rights reserved
Showing items related by title, author, creator and subject.
Saffari, S.; Adnan, R.; Greene, William; Ahmad, M. (2013)Typically, a Poisson regression model is assumed for count data. In many cases, there are many zeros in the dependent variable, therefore the mean is not equal to the variance value of the dependent variable. Thus, we ...
Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumptionGreene, W.; Harris, Mark N.; Srivastava, P.; Zhao, X. (2017)When modelling "social bads," such as illegal drug consumption, researchers are often faced with a dependent variable characterised by a large number of zero observations. Building on the recent literature on hurdle and ...
Tropical influenza and weather variability among children in an urban low-income population in BangladeshImai, C.; Brooks, W.; Chung, Y.; Goswami, D.; Anjali, B.; Dewan, Ashraf; Kim, H.; Hashizume, M. (2014)Background: Influenza seasonality in the tropics is poorly understood and not as well documented as intemperate regions. In addition, low-income populations are considered highly vulnerable to such acute respiratory ...