Comparing conditional survival functions with missing population marks in a competing risks model
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Comparing conditional survival functions with missing population marks in a competing risks modelDate
2016-11-25Citation
Bandyopadhyay, D., Jácome, M.A., 2016. Comparing conditional survival functions with missing population marks in a competing risks model. Computational Statistics & Data Analysis 95, 150–160. https://doi.org/10.1016/j.csda.2015.10.001
Abstract
[Abstract] In studies involving nonparametric testing of the equality of two or more survival distributions, the survival curves can exhibit a wide variety of behaviors such as proportional hazards, early/late differences, and crossing hazards. As alternatives to the classical logrank test, the weighted Kaplan–Meier (WKM) type statistic and their variations were developed to handle these situations. However, their applicability is limited to cases where the population membership is available for all observations, including the right censored ones. Quite often, failure time data are confronted with missing population marks for the censored observations. To alleviate this, a new WKM-type test is introduced based on imputed population marks for the censored observations leading to fractional at-risk sets that estimate the underlying risk for the process. The asymptotic normality of the proposed test under the null hypothesis is established, and the finite sample properties in terms of empirical size and power are studied through a simulation study. Finally, the new test is applied on a study of subjects undergoing bone marrow transplantation.
Keywords
Competing risk
Fractional risk set
Logrank test
Right censoring
Weighted Kaplan-Meier
Fractional risk set
Logrank test
Right censoring
Weighted Kaplan-Meier
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Rights
Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
1872-7352
0167-9473
0167-9473