We consider a comparison between the Kaplan-Meier and the semiparametric
estimators for a censorship models. The observations are assumed
to be generated under a semi-parametric random censorship, this mean that a
random censorship model where de conditional expectation of censoring indicator
given the observations belongs to a parametric family. The semi-parametric
estimator of the survival function was de ned in de U~na-Alvarez and Amorim
(2011). An asymptotic representation of a general empirical integral as a sum
of independent and identically distributed (i.i.d.) random variables under the
proposed model was obtained in Amorim (2012). The performance of the corresponding
asymptotic con dence intervals (a.c.i.) relative to that of a nonparametric
method, de U~na-Alvarez and Meira-Machado (2008), is investigated through
simulations Dikta et al. (2005).Project UID/MAT/00013/2013 - FCT - Fundação para a Ciência e a Tecnologi