  The two-parameter Birnbaum-Saunders distribution has been used succesfully to
model fatigue failure times. Although censoring is typical in reliability and
survival studies, little work has been published on the analysis of censored
data for this distribution. In this paper, we address the issue of performing
testing inference on the two parameters of the Birnbaum-Saunders distribution
under type-II right censored samples. The likelihood ratio statistic and a
recently proposed statistic, the gradient statistic, provide a convenient
framework for statistical inference in such a case, since they do not require
to obtain, estimate or invert an information matrix, which is an advantage in
problems involving censored data. An extensive Monte Carlo simulation study is
carried out in order to investigate and compare the finite sample performance
of the likelihood ratio and the gradient tests. Our numerical results show
evidence that the gradient test should be preferred. Three empirical
applications are presented.
