Nonparametric estimation with left-truncated and right-censored data when the sample size before truncation is known |
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Authors: | Pao-sheng Shen |
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Affiliation: | 1. Department of Statistics, Tunghai University, Taichung 40704, Taiwanpsshen@thu.edu.tw |
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Abstract: | In this article, we consider nonparametric estimation of the survival function when the data are subject to left-truncation and right-censoring and the sample size before truncation is known. We propose two estimators. The first estimator is derived based on a self-consistent estimating equation. The second estimator is obtained by using the constrained expectation-maximization algorithm. Simulation results indicate that both estimators are more efficient than the product-limit estimator. When there is no censoring, the performance of the proposed estimators is compared with that of the estimator proposed by Li and Qin [Semiparametric likelihood-based inference for biased and truncated data when total sample size is known, J. R. Stat. Soc. B 60 (1998), pp. 243–254] via simulation study. |
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Keywords: | self-consistency EM algorithm inverse-probability-weighted estimator |
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