ABSTRACT
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The literature on failure time data analysis has been growing fast and this
is especially the case in recent years for interval-censored failure time data, a
type of failure time data that often occurs in clinical trials and longitudinal
studies with periodic follow-ups, among others (Finkelstein (1986); Kalbfleisch
and Prentice (2002); Sun (2006)). In these situations, an individual due for
4 Interval-Censored Time-to-Event Data: Methods and Applications
the prescheduled observations for a clinically observable change in disease or
health status may miss some observations and return with a changed status.
Accordingly, we only know that the true event time is greater than the last
observation time at which the change has not occurred and less than or equal to
the first observation time at which the change has been observed to occur, thus
giving an interval that contains the real (but unobserved) time of occurrence
of the change. The well-studied right-censored failure time data are a special
case of interval-censored data.
