A Bezier curve method in interval-censored data

In this paper we propose a Bezier curve method to estimate the survival function and the median survival time in interval-censored data. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum like...

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Bibliographic Details
Published inJournal of the Korean Statistical Society Vol. 43; no. 4; pp. 621 - 629
Main Authors Yun, Eunyoung, Kim, Jinmi, Kim, Choongrak
Format Journal Article
LanguageEnglish
Published Singapore Elsevier B.V 01.12.2014
Springer Singapore
한국통계학회
Subjects
Applied Statistics
Bayesian Inference
Imputation method
Kaplan–Meier estimator
Median survival time
Statistical Theory and Methods
Statistics
Statistics and Computing/Statistics Programs
Survival function
통계학
Kaplan–Meier estimator
62N01
62N02
Survival function
Imputation method
Median survival time
Kaplan-Meier estimator
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Summary:In this paper we propose a Bezier curve method to estimate the survival function and the median survival time in interval-censored data. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies, and it is shown that the proposed estimator performs better than others in the sense of mean squared error and mean integrated squared error. An illustrative example based on a real data set is given.
Bibliography:G704-000337.2014.43.4.004
ISSN:1226-3192
2005-2863
DOI:10.1016/j.jkss.2014.01.006