A multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring
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Published on: January 11, 2020
Yue Zhao1, Amy H Herring, Haibo Zhou
1a Duke Clinical Research Institute , Durham , North Carolina , USA.
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.
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