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

Abstract:

We introduce a general nonparametric independence test between right-censored survival times and covariates, which may be multivariate. Our test statistic has a dual interpretation, first in terms of the supremum of a potentially infinite collection of weight-indexed log-rank tests, with weight functions belonging to a reproducing kernel Hilbert space (RKHS) of functions; and second, as the norm of the difference of embeddings of certain finite measures into the RKHS, similar to the Hilbert–S...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1080/01621459.2021.1961784

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Mansfield College
Role:
Author
ORCID:
0000-0001-5547-9213
Publisher:
Taylor and Francis
Journal:
Journal of the American Statistical Association More from this journal
Volume:
118
Issue:
542
Pages:
925-936
Publication date:
2021-09-13
Acceptance date:
2021-07-15
DOI:
EISSN:
1537-274X
ISSN:
0162-1459
Language:
English
Keywords:
Pubs id:
1084969
Local pid:
pubs:1084969
Deposit date:
2021-09-06

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