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A Comparative Study of Observation- and Parameter-driven Zero-inflated Poisson Models for Longitudinal Count Data
- Source :
- Communications in Statistics - Simulation and Computation. 45:3643-3659
- Publication Year :
- 2014
- Publisher :
- Informa UK Limited, 2014.
-
Abstract
- Longitudinal count data with excessive zeros frequently occur in social, biological, medical, and health research. To model such data, zero-inflated Poisson (ZIP) models are commonly used, after separating zero and positive responses. As longitudinal count responses are likely to be serially correlated, such separation may destroy the underlying serial correlation structure. To overcome this problem recently observation- and parameter-driven modelling approaches have been proposed. In the observation-driven model, the response at a specific time point is modelled through the responses at previous time points after incorporating serial correlation. One limitation of the observation-driven model is that it fails to accommodate the presence of any possible over-dispersion, which frequently occurs in the count responses. This limitation is overcome in a parameter-driven model, where the serial correlation is captured through the latent process using random effects. We compare the results obtained by the two m...
- Subjects :
- Statistics and Probability
Separation (statistics)
Autocorrelation
Poisson distribution
Random effects model
01 natural sciences
010104 statistics & probability
03 medical and health sciences
symbols.namesake
0302 clinical medicine
Quasi-likelihood
Modeling and Simulation
Statistics
symbols
Zero-inflated model
030212 general & internal medicine
Poisson regression
0101 mathematics
Mathematics
Count data
Subjects
Details
- ISSN :
- 15324141 and 03610918
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Communications in Statistics - Simulation and Computation
- Accession number :
- edsair.doi...........e064aa3d79e18f2ebfdf5b08e3f11217