Product-limit Estimators and Cox Regression with Missing Censoring Information
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 589-601 |
| Journal / Publication | Scandinavian Journal of Statistics |
| Volume | 25 |
| Issue number | 4 |
| Publication status | Published - Dec 1998 |
| Externally published | Yes |
Link(s)
Abstract
The Kaplan-Meier estimator of a survival function requires that the censoring indicator is always observed. A method of survival function estimation is developed when the censoring indicators are missing completely at random (MCAR). The resulting estimator is a smooth functional of the Nelson-Aalen estimators of certain cumulative transition intensities. The asymptotic properties of this estimator are derived. A simulation study shows that the proposed estimator has greater efficiency than competing MCAR-based estimators. The approach is extended to the Cox model setting for the estimation of a conditional survival function given a covariate.
Research Area(s)
- Counting processes, Incomplete data, Nelson-Aalen estimators, Product integral, Right censorship
Bibliographic Note
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Citation Format(s)
Product-limit Estimators and Cox Regression with Missing Censoring Information. / McKeague, Ian W.; Subramanian, Sundarraman.
In: Scandinavian Journal of Statistics, Vol. 25, No. 4, 12.1998, p. 589-601.
In: Scandinavian Journal of Statistics, Vol. 25, No. 4, 12.1998, p. 589-601.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
