Journal
ANNALS OF STATISTICS
Volume 36, Issue 3, Pages 1064-1089Publisher
INST MATHEMATICAL STATISTICS
DOI: 10.1214/009053607000000983
Keywords
survival analysis; current status data; competing risks; maximum likelihood; limiting distribution
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Funding
- NIAID NIH HHS [R37 AI029168, R37 AI029168-19] Funding Source: Medline
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We study nonparametric estimation for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler naive estimator. Groeneboom, Maathuis and Wellner [Ann. Statist. (2008) 36 10311063] proved that both types of estimators converge globally and locally at rate n(1/3). We use these results to derive the local limiting distributions of the estimators. The limiting distribution of the naive estimator is given by the slopes of the convex minorants of correlated Brownian motion processes with parabolic drifts. The limiting distribution of the MLE involves a new self-induced limiting process. Finally, we present a simulation study showing that the MLE is superior to the naive estimator in terms of mean squared error, both for small sample sizes and asymptotically.
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