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

Publication ,  Journal Article
Rahbar, MH; Choi, S; Hong, C; Zhu, L; Jeon, S; Gardiner, JC
Published in: PLoS One
2018

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.

Duke Scholars

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2018

Volume

13

Issue

5

Start / End Page

e0197295

Location

United States

Related Subject Headings

  • Wounds and Injuries
  • Time-to-Treatment
  • Time Factors
  • Survival Analysis
  • Statistics, Nonparametric
  • Prospective Studies
  • Multicenter Studies as Topic
  • Humans
  • General Science & Technology
  • Data Interpretation, Statistical
 

Citation

APA
Chicago
ICMJE
MLA
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Rahbar, M. H., Choi, S., Hong, C., Zhu, L., Jeon, S., & Gardiner, J. C. (2018). Nonparametric estimation of median survival times with applications to multi-site or multi-center studies. PLoS One, 13(5), e0197295. https://doi.org/10.1371/journal.pone.0197295
Rahbar, Mohammad H., Sangbum Choi, Chuan Hong, Liang Zhu, Sangchoon Jeon, and Joseph C. Gardiner. “Nonparametric estimation of median survival times with applications to multi-site or multi-center studies.PLoS One 13, no. 5 (2018): e0197295. https://doi.org/10.1371/journal.pone.0197295.
Rahbar MH, Choi S, Hong C, Zhu L, Jeon S, Gardiner JC. Nonparametric estimation of median survival times with applications to multi-site or multi-center studies. PLoS One. 2018;13(5):e0197295.
Rahbar, Mohammad H., et al. “Nonparametric estimation of median survival times with applications to multi-site or multi-center studies.PLoS One, vol. 13, no. 5, 2018, p. e0197295. Pubmed, doi:10.1371/journal.pone.0197295.
Rahbar MH, Choi S, Hong C, Zhu L, Jeon S, Gardiner JC. Nonparametric estimation of median survival times with applications to multi-site or multi-center studies. PLoS One. 2018;13(5):e0197295.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2018

Volume

13

Issue

5

Start / End Page

e0197295

Location

United States

Related Subject Headings

  • Wounds and Injuries
  • Time-to-Treatment
  • Time Factors
  • Survival Analysis
  • Statistics, Nonparametric
  • Prospective Studies
  • Multicenter Studies as Topic
  • Humans
  • General Science & Technology
  • Data Interpretation, Statistical