Nonparametric estimation of the cumulative incidences of competing risks under double truncation

Registry data typically report incident cases within a certain calendar time interval. Such interval sampling induces double truncation on the incidence times, which may result in an observational bias. In this paper, we introduce nonparametric estimation for the cumulative incidences of competing r...

Full description

Saved in:
Bibliographic Details
Published in:Biometrical journal 2020-05, Vol.62 (3), p.852-867
Main Author: de Uña‐Álvarez, Jacobo
Format: Article
Language:English
Subjects:
Age composition
Asymptotic properties
Cancer
Children
Estimators
Health risk assessment
interval sampling
multi‐state data
Nonparametric statistics
survival analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Registry data typically report incident cases within a certain calendar time interval. Such interval sampling induces double truncation on the incidence times, which may result in an observational bias. In this paper, we introduce nonparametric estimation for the cumulative incidences of competing risks when the incidence time is doubly truncated. Two different estimators are proposed depending on whether the truncation limits are independent of the competing events or not. The asymptotic properties of the estimators are established, and their finite sample performance is investigated through simulations. For illustration purposes, the estimators are applied to childhood cancer registry data, where the target population is peculiarly defined conditional on future cancer development. Then, in our application, the cumulative incidences inform on the distribution by age of the different types of cancer.
ISSN:0323-3847
1521-4036
DOI:10.1002/bimj.201800323