The Log-Logistic Regression Model Under Censoring Scheme.

A regression model, based on the well-known log-logistic distribution is proposed. This model is parameterized in terms of the median of the distribution, through a link function. The regression model assumes the censored data structure. The unknown parameters are estimated by maximum likelihood. Monte Carlo simulations with censoring and application to real censored data show the good quality of the proposed regression model. [ABSTRACT FROM AUTHOR]