Administrative and artificial censoring in censored regression models
Article first published online: 13 JUL 2001
Copyright © 2001 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 20, Issue 15, pages 2287–2304, 15 August 2001
How to Cite
Joffe, M. M. (2001), Administrative and artificial censoring in censored regression models. Statist. Med., 20: 2287–2304. doi: 10.1002/sim.850
- Issue published online: 13 JUL 2001
- Article first published online: 13 JUL 2001
- Manuscript Accepted: SEP 2000
- Manuscript Received: MAY 1998
- United States National Heart, Lung and Blood Institute. Grant Number: R29 HL59184
Administrative censoring, in which potential censoring times are known even for subjects who fail, is common in clinical and epidemiologic studies. Nonetheless, most statistical methods for failure-time data do not use the information contained in these potential censoring times. Robins has proposed two approaches for using this information to estimate parameters in an accelerated failure-time model; the methods generally require the analyst to treat as censored some subjects whose failure time is observed. This paper provides a rationale for this ‘artificial censoring’, discusses some of its consequences, and illustrates some of these points with data from a randomized trial of breast cancer screening. Copyright © 2001 John Wiley & Sons, Ltd.