Abstract
The author proposes a nonparametric test for checking the lack of fit of the quantile function of survival time given the covariates; she assumes that 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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 321-336 |
| Number of pages | 16 |
| Journal | Canadian Journal of Statistics |
| Volume | 36 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2008 |
| Externally published | Yes |
Keywords
- Conditional moment
- Hypothesis testing
- Lack of fit
- Model checking
- Quantile regression
- Random censoring
- Test
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