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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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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. |
format | Online Article Text |
id | pubmed-5957417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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