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http://dx.doi.org/10.5351/KJAS.2014.27.6.923

Hurdle Model for Longitudinal Zero-Inflated Count Data Analysis  

Jin, Iktae (Department of Statistics, Sungkyunkwan University)
Lee, Keunbaik (Department of Statistics, Sungkyunkwan University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.6, 2014 , pp. 923-932 More about this Journal
Abstract
The Hurdle model can to analyze zero-inflated count data. This model is a mixed model of the logit model for a binary component and a truncated Poisson model of a truncated count component. We propose a new hurdle model with a general heterogeneous random effects covariance matrix to analyze longitudinal zero-inflated count data using modified Cholesky decomposition. This decomposition factors the random effects covariance matrix into generalized autoregressive parameters and innovation variance. The parameters are modeled using (generalized) linear models and estimated with a Bayesian method. We use these methods to carefully analyze a real dataset.
Keywords
Random effects covariance matrix; generalized linear model; modified Cholesky decomposition; truncated Poisson model;
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Times Cited By KSCI : 1  (Citation Analysis)
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