  We propose a novel approach for estimating mean survival time in the presence
of censored data, in which we divide the population under study into
survival-ordered fractions defined by a set of proportions, and compute the
mean survival time for each fraction separately. Our approach provides a
detailed picture of the distribution of the time variable while preserving the
appealing interpretation of the mean. Our measure proves to be of great use in
applications, particularly those where we are able to detect differences in
mean survival across groups for certain fractions of the population that would
have been overlooked using other available methods.
