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Optimal Weighted Wilcoxon–Mann–Whitney Test for Prioritized Outcomes Read chapter Read first chapter

2018 | OriginalPaper | Chapter

22. Nonparametric Estimation of a Hazard Rate Function with Right Truncated Data

Authors : Haci Akcin, Xu Zhang, Yichuan Zhao

Published in: New Frontiers of Biostatistics and Bioinformatics

Publisher: Springer International Publishing

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Abstract

Left truncation and right truncation coexist in a truncated sample. Earlier researches focused on left truncation. Lagakos et al. (Biometrika 75:515–523, 1988) proposed to transform right truncated data to left truncated data and then apply the methods developed for left truncation. Interpretation of survival quantities, such as the hazard rate function, in reverse-time is not natural. Though it is most interpretable, researchers seldom use the forward-time hazard function. In this book chapter we studied the nonparametric inference for the hazard rate function with right truncated data. Kernel smoothing techniques were used to get smoothed estimates of hazard rates. Three commonly used kernels, uniform, Epanechnikov, and biweight kernels were applied on the AIDS data to illustrate the proposed methods.

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previous chapter Empirical Study on High-Dimensional Variable Selection and Prediction Under Competing Risks
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Metadata
Title
Nonparametric Estimation of a Hazard Rate Function with Right Truncated Data
Authors
Haci Akcin
Xu Zhang
Yichuan Zhao
Copyright Year
2018
Book
New Frontiers of Biostatistics and Bioinformatics

Print ISBN: 978-3-319-99388-1

Electronic ISBN: 978-3-319-99389-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-99389-8_22

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