On Baseline Conditions For Zero-Inflated Longitudinal Count Data
AbstractWe describe a mixed-effects hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations. We show how model parameters can be estimated in a fnite mixture context, allowing for overdispersion, multivariate association and endogeneity of the baseline variable. The model behavior is investigated through a large scale simulation experiment. An empirical example on health care utilization data is provided.
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Bibliographic InfoPaper provided by CREI Università degli Studi Roma Tre in its series Working Papers with number 0212.
Length: 27 pages
Date of creation: 2012
Date of revision: 2012
Hurdle model - Baseline conditions - Longitudinal count data - Zero-inflation.;
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