TITLE:
The Statistical Analysis of Interval-Censored Failure Time Data with Applications
AUTHORS:
Radhey S. Singh, Dishna P. Totawattage
KEYWORDS:
Interval Cens oring; Survival Analysis; Parametric;Non-Parametric; Semi-Parametric; Survival Functions; Survival Curves; Kaplan-Meier Estimate; Turnbull Estimator; Logspline Estimation
JOURNAL NAME:
Open Journal of Statistics,
Vol.3 No.2,
April
30,
2013
ABSTRACT:
The analysis of survival data is a major focus of
statistics. Interval censored data reflect uncertainty as to the exact times
the units failed within an interval. This type of data frequently comes from
tests or situations where the objects of interest are not
constantly monitored. Thus events are known only to have occurred between the
two observation periods. Interval censoring has become increasingly common in
the areas that produce failure time data. This paper explores
the statistical analysis of interval-censored failure time data with
applications. Three different data sets, namely Breast Cancer, Hemophilia, and
AIDS data were used to illustrate the methods during this study. Both
parametric and nonparametric methods of analysis are carried out in this study. Theory
and methodology of fitted models for the interval-censored data
are described. Fitting of parametric and non-parametric models to three real
data sets are considered. Results derived from different methods are presented
and also compared.