  We propose a new continuous-discrete mixture regression model which is useful
for describing highly censored data. We motivate our investigation based on a
case-study in biometry related to measles vaccines in Haiti. In this
case-study, the neutralization antibody level is explained by the type of
vaccine used, level of the dosage and gender of the patient. This mixture model
allows us to account for excess of censored observations and consists of the
Birnbaum-Saunders and Bernoulli distributions. These distributions describe the
antibody level and the point mass of the censoring observations. We estimate
the model parameters with the maximum likelihood method. Numerical evaluation
of the model is performed by Monte Carlo simulations and by an illustration
with biometrical data, both of which show its good performance and its
potential applications.
