A multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring.

TitleA multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring.
Publication TypeJournal Article
Year of Publication2014
AuthorsZhao, Yue, Amy H. Herring, Haibo Zhou, Mirza W. Ali, and Gary G. Koch
JournalJ Biopharm Stat
Volume24
Issue2
Pagination229-53
Date Published2014
ISSN1520-5711
KeywordsClinical Trials as Topic, Data Interpretation, Statistical, Follow-Up Studies, Humans, Kaplan-Meier Estimate, Time Factors, Withholding Treatment
Abstract

This article presents a multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring. The imputed time for censored values is drawn from the failure time distribution conditional on the time of follow-up discontinuation. A variety of specifications regarding the post-discontinuation tendency of having events can be incorporated in the imputation through a hazard ratio parameter for discontinuation versus continuation of follow-up. Multiple-imputed data sets are analyzed with the primary analysis method, and the results are then combined using the methods of Rubin. An illustrative example is provided.

DOI10.1080/10543406.2013.860769
Alternate JournalJ Biopharm Stat
Original PublicationA multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring.
PubMed ID24605967
PubMed Central IDPMC4009741
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 ES021900 / ES / NIEHS NIH HHS / United States
Project: