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Administrative and artificial censoring in censored regression models
Author(s) -
Joffe Marshall M.
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.850
Subject(s) - censoring (clinical trials) , accelerated failure time model , computer science , statistics , econometrics , survival analysis , regression analysis , regression , mathematics
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.