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Survival Data with Measurement Error

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Statistical Analysis with Measurement Error or Misclassification

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Abstract

Survival analysis is commonly challenged by the presence of covariate measurement error. Biomarkers, such as blood pressure, cholesterol level, and CD4 counts, are subject to measurement error due to biological variability and other sources of variation. It is known that standard inferential procedures often produce seriously biased estimation if measurement error is not properly taken into account. Since the seminal paper by Prentice (1982), there has been a large number of research papers devoted to handling covariate measurement error for survival data.

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    Grace Y. Yi

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Yi, G.Y. (2017). Survival Data with Measurement Error. In: Statistical Analysis with Measurement Error or Misclassification. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6640-0_3

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