Convergence Rate of Survival Function Estimator for Randomly Right-Censored Data

2018 ◽  
Author(s):  
Petr A. Philonenko ◽  
Sergey N. Postovalov
Keyword(s):  
Convergence Rate ◽  
Censored Data ◽  
Survival Function ◽  
Right Censored Data

An extension of generalized pairwise comparisons for prioritized outcomes in the presence of censoring

2016 ◽  
Vol 27 (4) ◽  
pp. 1230-1239 ◽  
Author(s):  
Julien Péron ◽  
Marc Buyse ◽  
Brice Ozenne ◽  
Laurent Roche ◽  
Pascal Roy
Keyword(s):  
Censored Data ◽  
Type I Error ◽  
Standard Procedure ◽  
Survival Function ◽  
Control Group ◽  
Pairwise Comparisons ◽  
Type I ◽  
Time To Event ◽  
Right Censored Data ◽  
Higher Power

Generalized pairwise comparisons have been proposed to permit a comprehensive assessment of several prioritized outcomes between two groups of observations. This procedure estimates Δ, the net chance of a better outcome with treatment than with control by comparing the patients outcomes among all possible pairs taking one patient from the treatment group and one patient from the control group. For time to event outcomes, the standard procedure of generalized pairwise comparisons is analogous to the Gehan’s modification of the Mann-Whitney test which is biased in presence of censored observation and less powerful than Efron’s modification of this test. We adapt Efron’s modification to generalized pairwise comparisons. We show how a pairwise contribution to Δ can be calculated from the estimates of the survival function in the presence of right-censored data. We performed a simulation study to assess the bias, the type I error and the power of the new procedure. The estimate of Δ with the new procedure is only slightly biased even in presence of heavy censoring. We also show how this bias can be corrected when only one time-to-event outcome is analyzed. The new procedure has higher power in most cases compared to the standard procedure.

Estimation of Bivariate Survival Function from Random Censored Data with Poisson Sample Size

2020 ◽  
Vol 72 (2) ◽  
pp. 111-121
Author(s):  
Abdurakhim Akhmedovich Abdushukurov ◽  
Rustamjon Sobitkhonovich Muradov
Keyword(s):  
Relative Risk ◽  
Sample Size ◽  
Censored Data ◽  
Survival Function ◽  
Survival Functions ◽  
Power Structures ◽  
Bivariate Survival ◽  
Empirical Estimates ◽  
Bivariate Survival Function ◽  
Product Limit

At the present time there are several approaches to estimation of survival functions of vectors of lifetimes. However, some of these estimators either are inconsistent or not fully defined in range of joint survival functions and therefore not applicable in practice. In this article, we consider three types of estimates of exponential-hazard, product-limit, and relative-risk power structures for the bivariate survival function, when replacing the number of summands in empirical estimates with a sequence of Poisson random variables. It is shown that these estimates are asymptotically equivalent. AMS 2000 subject classification: 62N01

scholarly journals Weighted expectile regression for right‐censored data

2021 ◽  
Author(s):  
Alexander Seipp ◽  
Verena Uslar ◽  
Dirk Weyhe ◽  
Antje Timmer ◽  
Fabian Otto‐Sobotka
Keyword(s):  
Censored Data ◽  
Right Censored Data ◽  
Expectile Regression

scholarly journals A kernel log-rank test of independence for right-censored data

2021 ◽  
pp. 1-26
Author(s):  
Tamara Fernández ◽  
Arthur Gretton ◽  
David Rindt ◽  
Dino Sejdinovic
Keyword(s):  
Censored Data ◽  
Rank Test ◽  
Right Censored Data ◽  
Test Of Independence ◽  
Log Rank Test
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