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A Multiple Imputation Method for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring

Citation

Zhao, Yue; Herring, Amy H.; Zhou, Haibo; Ali, Mirza W.; & Koch, Gary G. (2014). A Multiple Imputation Method for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring. Journal of Biopharmaceutical Statistics, 24(2), 229-253. PMCID: PMC4009741

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.

URL

http://dx.doi.org/10.1080/10543406.2013.860769

Reference Type

Journal Article

Year Published

2014

Journal Title

Journal of Biopharmaceutical Statistics

Author(s)

Zhao, Yue
Herring, Amy H.
Zhou, Haibo
Ali, Mirza W.
Koch, Gary G.

PMCID

PMC4009741