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Nonparametric estimation of median survival times with applications to multi-site or multi-center studies

We propose a nonparametric shrinkage estimator for the median survival times from several independent samples of right-censored data, which combines the samples and hypothesis information to improve the efficiency. We compare efficiency of the proposed shrinkage estimation procedure to unrestricted...

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Autores principales: Rahbar, Mohammad H., Choi, Sangbum, Hong, Chuan, Zhu, Liang, Jeon, Sangchoon, Gardiner, Joseph C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957417/
https://www.ncbi.nlm.nih.gov/pubmed/29772007
http://dx.doi.org/10.1371/journal.pone.0197295
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author Rahbar, Mohammad H.
Choi, Sangbum
Hong, Chuan
Zhu, Liang
Jeon, Sangchoon
Gardiner, Joseph C.
author_facet Rahbar, Mohammad H.
Choi, Sangbum
Hong, Chuan
Zhu, Liang
Jeon, Sangchoon
Gardiner, Joseph C.
author_sort Rahbar, Mohammad H.
collection PubMed
description We propose a nonparametric shrinkage estimator for the median survival times from several independent samples of right-censored data, which combines the samples and hypothesis information to improve the efficiency. We compare efficiency of the proposed shrinkage estimation procedure to unrestricted estimator and combined estimator through extensive simulation studies. Our results indicate that performance of these estimators depends on the strength of homogeneity of the medians. When homogeneity holds, the combined estimator is the most efficient estimator. However, it becomes inconsistent when homogeneity fails. On the other hand, the proposed shrinkage estimator remains efficient. Its efficiency decreases as the equality of the survival medians is deviated, but is expected to be as good as or equal to the unrestricted estimator. Our simulation studies also indicate that the proposed shrinkage estimator is robust to moderate levels of censoring. We demonstrate application of these methods to estimating median time for trauma patients to receive red blood cells in the Prospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study.
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spelling pubmed-59574172018-05-31 Nonparametric estimation of median survival times with applications to multi-site or multi-center studies Rahbar, Mohammad H. Choi, Sangbum Hong, Chuan Zhu, Liang Jeon, Sangchoon Gardiner, Joseph C. PLoS One Research Article We propose a nonparametric shrinkage estimator for the median survival times from several independent samples of right-censored data, which combines the samples and hypothesis information to improve the efficiency. We compare efficiency of the proposed shrinkage estimation procedure to unrestricted estimator and combined estimator through extensive simulation studies. Our results indicate that performance of these estimators depends on the strength of homogeneity of the medians. When homogeneity holds, the combined estimator is the most efficient estimator. However, it becomes inconsistent when homogeneity fails. On the other hand, the proposed shrinkage estimator remains efficient. Its efficiency decreases as the equality of the survival medians is deviated, but is expected to be as good as or equal to the unrestricted estimator. Our simulation studies also indicate that the proposed shrinkage estimator is robust to moderate levels of censoring. We demonstrate application of these methods to estimating median time for trauma patients to receive red blood cells in the Prospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study. Public Library of Science 2018-05-17 /pmc/articles/PMC5957417/ /pubmed/29772007 http://dx.doi.org/10.1371/journal.pone.0197295 Text en © 2018 Rahbar et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rahbar, Mohammad H.
Choi, Sangbum
Hong, Chuan
Zhu, Liang
Jeon, Sangchoon
Gardiner, Joseph C.
Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title_full Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title_fullStr Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title_full_unstemmed Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title_short Nonparametric estimation of median survival times with applications to multi-site or multi-center studies
title_sort nonparametric estimation of median survival times with applications to multi-site or multi-center studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957417/
https://www.ncbi.nlm.nih.gov/pubmed/29772007
http://dx.doi.org/10.1371/journal.pone.0197295
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