An improved survival estimator for censored medical costs with a kernel approach
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© 2018, © 2018 Taylor & Francis Group, LLC. Cost assessment serves as an essential part in economic evaluation of medical interventions. In many studies, costs as well as survival data are frequently censored. Standard survival analysis techniques are often invalid for censored costs, due to the induced dependent censoring problem. Owing to high skewness in many cost data, it is desirable to estimate the median costs, which will be available with estimated survival function of costs. We propose a kernel-based survival estimator for costs, which is monotone, consistent, and more efficient than several existing estimators. We conduct numerical studies to examine the finite-sample performance of the proposed estimator.
author list (cited authors)
Chen, S., Lu, W., & Zhao, H.