A kernel- and optimal transport- based test of independence between covariates and right-censored lifetimes
We propose a nonparametric test of independence, termed OPT-HSIC, between a covariate and a right-censored lifetime. Because the presence of censoring creates a challenge in applying the standard permutation-based testing approaches, we use optimal transport to transform the censored dataset into an...
| Автори: | , , |
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| Формат: | Journal article |
| Мова: | English |
| Опубліковано: |
De Gruyter
2020
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| Резюме: | We propose a nonparametric test of independence, termed OPT-HSIC, between a
covariate and a right-censored lifetime. Because the presence of censoring
creates a challenge in applying the standard permutation-based testing
approaches, we use optimal transport to transform the censored dataset into an
uncensored one, while preserving the relevant dependencies. We then apply a
permutation test using the kernel-based dependence measure as a statistic to
the transformed dataset. The type 1 error is proven to be correct in the case
where censoring is independent of the covariate. Experiments indicate that
OPT-HSIC has power against a much wider class of alternatives than Cox
proportional hazards regression and that it has the correct type 1 control even
in the challenging cases where censoring strongly depends on the covariate. |
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