Abstract
While the quantiles have many advantages including robustness, straightforward interpretation, and presentation of specific information, they also suffer from some pitfalls. First of all, evaluation of the variance formulas of the quantiles involves estimation of the probability density function under independent and/or dependent censoring. A method that was adopted to avoid this hurdle produced complicated variance formulas. Second, when the censoring proportion is high, higher quantiles cannot be defined. In this chapter, we review two recent approaches that address these issues; the empirical likelihood ratio-based method and a Bayesian method.
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Jeong, JH. (2014). Other Methods for Inference on Quantiles. In: Statistical Inference on Residual Life. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0005-3_5
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DOI: https://doi.org/10.1007/978-1-4939-0005-3_5
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