Nonparametric test for checking lack of fit of the quantile regression model under random censoring. (English) Zbl 1144.62032
Summary: The author proposes a nonparametric test for checking the lack of fit of the quantile function of the survival time given the covariates; she assumes that the survival time is subjected to random right censoring. Her test statistic is a kernel-based smoothing estimator of a moment condition. The test statistic is asymptotically Gaussian under the null hypothesis. The author investigates its behavior under local alternative sequences. She assesses its finite-sample power through simulations and illustrates its use with the Stanford heart transplant data.
MSC:
| 62G10 | Nonparametric hypothesis testing |
| 62N01 | Censored data models |
| 62G08 | Nonparametric regression and quantile regression |
| 62G20 | Asymptotic properties of nonparametric inference |
| 62N03 | Testing in survival analysis and censored data |
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