A Multiple Imputation Method for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring
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 re...
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| Veröffentlicht in: | Journal of biopharmaceutical statistics 2014-03, Vol.24 (2), p.229-253 |
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| container_title | Journal of biopharmaceutical statistics |
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| creator | Zhao, Yue Herring, Amy H. Zhou, Haibo Ali, Mirza W. Koch, Gary G. |
| description | 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. |
| doi_str_mv | 10.1080/10543406.2013.860769 |
| format | Article |
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| ispartof | Journal of biopharmaceutical statistics, 2014-03, Vol.24 (2), p.229-253 |
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| language | eng |
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| source | MEDLINE; EBSCOhost Business Source Complete |
| subjects | Clinical Trials as Topic - statistics & numerical data Data Interpretation, Statistical Failure times Follow-Up Studies Hazards Humans Information Kaplan-Meier Estimate Multiple imputation Sensitivity analysis Specifications Statistics Time Factors Time-to-event data Withholding Treatment - statistics & numerical data |
| title | A Multiple Imputation Method for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring |
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