A Multiple Imputation Approach to the Analysis of Current Status Data with the Additive Hazards Model |
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Authors: | Ling Chen Jianguo Sun |
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Affiliation: | 1. Department of Statistics , University of Missouri , Columbia, Missouri, USA lcbm9@mizzou.edu;3. Department of Statistics , University of Missouri , Columbia, Missouri, USA |
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Abstract: | This article discusses regression analysis of current status data, which occur in many fields including cross-sectional studies, demographical investigations, and tumorigenicity experiments (Keiding, 1991 Keiding , N. ( 1991 ). Age-specific incidence and prevalence: a statistical perspective (with discussion) . J. Roy. Statist. Soc. Ser. A 154 : 371 – 412 .[Crossref] , [Google Scholar]; Sun 2006 Sun , J. ( 2006 ). The Statistical Analysis of Interval-Censored Failure Time Data . New York : Springer-Verlag . [Google Scholar]). For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model and a multiple imputation approach is presented for inference. A major advantage of the approach is its simplicity and it can be easily implemented by using the existing software packages for right-censored failure time data. Extensive simulation studies are conducted and indicate that the approach performs well for practical situations and is comparable to the existing methods. The methodology is applied to a set of current status data arising from a tumorigenicity experiment and the model checking is discussed. |
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Keywords: | Additive hazards model Current status data Multiple imputation Tumorigenicity experiment |
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