Methods for Bivariate Survival Data with Mismeasured Covariates Under an Accelerated Failure Time Model |
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| Authors: | Grace Y Yi Wenqing He |
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| Institution: | 1. Department of Statistics and Actuarial Science , University of Waterloo , Waterloo , Ontario , Canada yyi@uwaterloo.ca;3. Department of Statistics and Actuarial Science , University of Western Ontario , London , Ontario , Canada |
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| Abstract: | Accelerated failure time models are useful in survival data analysis, but such models have received little attention in the context of measurement error. In this paper we discuss an accelerated failure time model for bivariate survival data with covariates subject to measurement error. In particular, methods based on the marginal and joint models are considered. Consistency and efficiency of the resultant estimators are investigated. Simulation studies are carried out to evaluate the performance of the estimators as well as the impact of ignoring the measurement error of covariates. As an illustration we apply the proposed methods to analyze a data set arising from the Busselton Health Study (Knuiman et al., 1994
Knuiman , M. W. ,
Cullent , K. J. ,
Bulsara , M. K. ,
Welborn , T. A. ,
Hobbs , M. S. T. ( 1994 ). Mortality trends, 1965 to 1989, in Busselton, the site of repeated health surveys and interventions . Austral. J. Public Health 18 : 129 – 135 . CSA] Crossref], PubMed] , Google Scholar]). |
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| Keywords: | Accelerated failure times Bivariate survival data Efficiency Measurement error Normal distributions Robustness |
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