Asymptotic properties of the maximum likelihood estimator in zero-inated binomial regression

International audience ; The zero-inated binomial (ZIB) regression model was proposed by Hall (2000) to account for excess zeros in binomial regression. Since then, the model has been applied in various elds, 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 lls 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 eld of health economics illustrates the paper.