Correction: Nonparametric Confidence Intervals for the Median in the Presence of Right Censoring

Biometrics ◽  
1983 ◽  
Vol 39 (4) ◽  
pp. 1137 ◽  
Keyword(s):  
Confidence Intervals ◽  
Right Censoring ◽  
Nonparametric Confidence Intervals

Nonparametric Confidence Intervals for the Median in the Presence of Right Censoring

Biometrics ◽  
1982 ◽  
Vol 38 (1) ◽  
pp. 17 ◽  
Author(s):  
John D. Emerson
Keyword(s):  
Confidence Intervals ◽  
Right Censoring ◽  
Nonparametric Confidence Intervals

scholarly journals Improved Nonparametric Confidence Intervals in Time Series Regressions

2003 ◽  
Author(s):  
Joseph P. Romano ◽  
Michael NMI Wolf
Keyword(s):  
Time Series ◽  
Confidence Intervals ◽  
Nonparametric Confidence Intervals

scholarly journals Nonparametric generalized fiducial inference for survival functions under censoring

Biometrika ◽  
2019 ◽  
Vol 106 (3) ◽  
pp. 501-518 ◽  
Author(s):  
Y Cui ◽  
J Hannig
Keyword(s):  
Confidence Intervals ◽  
Average Length ◽  
Asymptotic Methods ◽  
Survival Function ◽  
Right Censoring ◽  
Rank Tests ◽  
Fiducial Inference ◽  
Fiducial Distribution ◽  
Von Mises ◽  
Log Rank Tests

Summary Since the introduction of fiducial inference by Fisher in the 1930s, its application has been largely confined to relatively simple, parametric problems. In this paper, we present what might be the first time fiducial inference is systematically applied to estimation of a nonparametric survival function under right censoring. We find that the resulting fiducial distribution gives rise to surprisingly good statistical procedures applicable to both one-sample and two-sample problems. In particular, we use the fiducial distribution of a survival function to construct pointwise and curvewise confidence intervals for the survival function, and propose tests based on the curvewise confidence interval. We establish a functional Bernstein–von Mises theorem, and perform thorough simulation studies in scenarios with different levels of censoring. The proposed fiducial-based confidence intervals maintain coverage in situations where asymptotic methods often have substantial coverage problems. Furthermore, the average length of the proposed confidence intervals is often shorter than the length of confidence intervals for competing methods that maintain coverage. Finally, the proposed fiducial test is more powerful than various types of log-rank tests and sup log-rank tests in some scenarios. We illustrate the proposed fiducial test by comparing chemotherapy against chemotherapy combined with radiotherapy, using data from the treatment of locally unresectable gastric cancer.

scholarly journals Nonparametric confidence intervals for monotone functions

2015 ◽  
Vol 43 (5) ◽  
pp. 2019-2054 ◽  
Author(s):  
Piet Groeneboom ◽  
Geurt Jongbloed
Keyword(s):  
Confidence Intervals ◽  
Monotone Functions ◽  
Nonparametric Confidence Intervals

scholarly journals Smooth confidence intervals for the survival function under random right censoring

2012 ◽  
Vol 6 (0) ◽  
pp. 843-860 ◽  
Author(s):  
Dimitrios Bagkavos ◽  
Dimitrios Ioannides
Keyword(s):  
Confidence Intervals ◽  
Survival Function ◽  
Right Censoring
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