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The effect of classification errors in survival data analysis

机译:分类错误对生存数据分析的影响

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Survival data analysis aims at collecting data on durations spent in a state by a sample of units, in order to analyse the process of transition to a different state. Survival analysis applied to social and economic phenomena typically relies upon data on transitions collected, for a sample of units, in one or more follow-up surveys. We explore the effect of misclassification of the transition indicator on parameter estimates in an appropriate statistical model for the duration spent in an origin state. Some empirical investigations about the bias induced when ignoring misclassification are reported, extending the model to include the possibility that the rate of misclassification can vary across units according to the value of some covariates. Finally it is shown how a Bayesian approach can lead to parameter estimates.
机译:生存数据分析旨在通过单位样本收集有关某个状态所花费的持续时间的数据,以便分析过渡到不同状态的过程。应用于社会和经济现象的生存分析通常依赖于在一个或多个后续调查中针对单位样本收集的过渡数据。我们探索在原始状态下花费的持续时间的适当统计模型中,过渡指标分类错误对参数估计值的影响。报告了一些有关忽略分类错误时引起的偏见的实证研究,将模型扩展到包括以下可能性:分类错误率可能会根据某些协变量的值在各个单位之间变化。最后显示了贝叶斯方法如何导致参数估计。

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