Journal
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume 46, Issue 20, Pages 9930-9948Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610926.2016.1222437
Keywords
Asymptotic normality; consistency; count data; excess of zeros; simulations
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Funding
- Service de Cooperation et d'Action Culturelle of the French Embassy in Senegal
- CEA-MITIC (African Center of Excellence in Mathematics, Informatics)
- ICT
- Gaston Berger University (Senegal)
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The zero-inflated binomial (ZIB) regression model was proposed to account for excess zeros in binomial regression. Since then, the model has been applied in various fields, such as ecology and epidemiology. In these applications, maximum-likelihood estimation (MLE) is used to derive parameter estimates. However, theoretical properties of the MLE in ZIB regression have not yet been rigorously established. The current paper fills this gap and thus provides a rigorous basis for applying the model. Consistency and asymptotic normality of the MLE in ZIB regression are proved. A consistent estimator of the asymptotic variance-covariance matrix of the MLE is also provided. Finite-sample behavior of the estimator is assessed via simulations. Finally, an analysis of a data set in the field of health economics illustrates the paper.
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