Randomly left or right truncated observations occur when one is concerned with estimation of the distribution of time between two events and when one only observes the time if one of the two events falls in a fixed time-window, so that longer survivial times have higher probability to be part of the
Survival function and density estimation for truncated dependent data
β Scribed by Liuquan Sun; Xian Zhou
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 118 KB
- Volume
- 52
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
In some long-term studies, a series of dependent and possibly truncated lifetimes may be observed. Suppose that the lifetimes have a common marginal distribution function. Under some regularity conditions, we provide a strong representation of the product-limit estimator in the form of an average of random variables plus a remainder term. In addition, we also give asymptotic representations for the kernel estimators of the density and the hazard rate. These representations enable us to obtain the asymptotic normality and the uniform consistency of the estimators.
π SIMILAR VOLUMES
A strong i.i.d. representation is obtained for the product-limit estimator of the survival function based on left truncated and right censored data. This extends the result of Chao and Lo (1988, Ann. Statist. 16, 661-668) for truncated data. An improved rate of the approximation is also obtained on
In some long term studies, a series of dependent and possibly censored failure times may be observed. Suppose that the failure times have a common marginal distribution function having a density, and the nonparametric estimation of density and hazard rate under random censorship is of our interest.
## Abstract The performance of clinical tests for disease screening is often evaluated using the area under the receiverβoperating characteristic (ROC) curve (AUC). Recent developments have extended the traditional setting to the AUC with binary timeβvarying failure status. Without considering cova