Abstract
The cumulative hazard function plays an important role not only in survival analysis in biostatistical applications, but also in many other fields including finance and reliability analysis. When the data size exceeds the computer memory, many traditional nonparametric approaches for estimating and testing the cumulative hazard function are not applicable. In this chapter, we develop an online updating nonparametric estimation method for the cumulative hazard function and propose an online testing procedure for equality of cumulative hazard functions under a two-group setting, both based on the empirical likelihood method. Under reasonable regularity conditions, we show several asymptotic properties of our proposed estimator and test statistic. Their performance is illustrated with extensive simulation studies and with an application to a large lymphoma cancer dataset from the Surveillance, Epidemiology, and End Results (SEER) Program.
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Xue, Y., Schifano, E.D., Hu, G. (2021). Online Updating of Nonparametric Survival Estimator and Nonparametric Survival Test. In: Zhao, Y., Chen, (.DG. (eds) Modern Statistical Methods for Health Research. Emerging Topics in Statistics and Biostatistics . Springer, Cham. https://doi.org/10.1007/978-3-030-72437-5_18
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DOI: https://doi.org/10.1007/978-3-030-72437-5_18
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