A discrete time sequential method for analyzing censored
survival data
ABSTRACT:
A sequential testing procedure for comparing survival distributions with
binary responses is considered. The data are monitored according to a
discrete time process of reviewing the situation at regularly spaced
intervals of time by using the likelihood ratio as a test statistic.
Sampling continues until either a decision can be made about the hazard
rates characterizing the survival distributions to be compared or a
prespecified time limit is reached. Monte Carlo simulations are used to
model and estimate the power of the process. More specifically, the
critical threshold which allows one to control type-I error at a given
level during the whole testing procedure is also determined empirically
by simulation. Particular attention is paid to the gain of efficiency
resulting from the sequential approach. The better understanding of the
relative incidence of the parameters defining the experimental
conditions on the power of the process is shown to be helpful in
planning a proper experimental design for a wide range of comparative
studies (e. g. clinical trials, environmental health studies). The
method is illustrated by two numerical examples referring to: (i)
survival data of couples trying to begin a pregnancy, and (ii) the
incidence of childhood leukaemia around a nuclear reprocessing plant.
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