Buckley–James-Type Estimator with Right-Censored and Length-Biased Data
Article first published online: 8 MAR 2011
© 2011, The International Biometric Society
Volume 67, Issue 4, pages 1369–1378, December 2011
How to Cite
Ning, J., Qin, J. and Shen, Y. (2011), Buckley–James-Type Estimator with Right-Censored and Length-Biased Data. Biometrics, 67: 1369–1378. doi: 10.1111/j.1541-0420.2011.01568.x
- Issue published online: 14 DEC 2011
- Article first published online: 8 MAR 2011
- Received April 2010. Revised October 2010. Accepted December 2010.
- Accelerated failure time model;
- Buckley–James estimator;
- Estimating equation;
- Length-biased sampling;
- Prevalent cohort
Summary We present a natural generalization of the Buckley–James-type estimator for traditional survival data to right-censored length-biased data under the accelerated failure time (AFT) model. Length-biased data are often encountered in prevalent cohort studies and cancer screening trials. Informative right censoring induced by length-biased sampling creates additional challenges in modeling the effects of risk factors on the unbiased failure times for the target population. In this article, we evaluate covariate effects on the failure times of the target population under the AFT model given the observed length-biased data. We construct a Buckley–James-type estimating equation, develop an iterative computing algorithm, and establish the asymptotic properties of the estimators. We assess the finite-sample properties of the proposed estimators against the estimators obtained from the existing methods. Data from a prevalent cohort study of patients with dementia are used to illustrate the proposed methodology.