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Biometrika 2003 90(1):183-197; doi:10.1093/biomet/90.1.183
© 2003 by Biometrika Trust
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Nonparametric estimation from current status data with competing risks

Nicholas P.Jewell1, Mark van der Laan1 and Tanya Henneman1

1 Division of Biostatistics, School of Public Health, University of California, Berkeley, California 94720, U.S.Ajewell{at}stat.berkeley.edu laan{at}stat.berkeley.edu thenn{at}ucla.edu

A great deal of recent attention has focused on the estimation of survival distributions based on current status data, an extreme form of interval censored data.This particular data structure arises in a wide variety of applications where cross-sectional observation either naturally occurs or is preferred to more traditional forms of follow-up. Here we consider current status data in the context of competing risks. We briefly consider simple parametric models as a backdrop to nonparametric procedures. We make some brief comparisons and remarks regarding the nonparametric maximum likelihood estimator. The ideas are illustrated on the data of Krailo & Pike (1983) which considers estimation of the age distribution at both natural and operative menopause. We also consider the case where there is exact observation of failure times due to one of the competing risks when failure occurs prior to the monitoring time.

Key Words: Competing risks; Current status data; Nonparametric maximum likelihood estimation

Received August 2001. Revised February 2002


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