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A nonparametric test for the association between longitudinal covariates and censored survival data

Author
Oller, R.; Gómez Melis, Guadalupe
Type of activity
Journal article
Journal
Biostatistics
Date of publication
2020-10-01
Volume
21
Number
4
First page
727
Last page
742
DOI
10.1093/biostatistics/kxz002
Repository
http://hdl.handle.net/2117/345512 Open in new window
URL
https://academic.oup.com/biostatistics/article-abstract/21/4/727/5364035 Open in new window
Abstract
Many biomedical studies focus on the association between a longitudinal measurement and a time-to-event outcome while quantifying this association by means of a longitudinal-survival joint model. In this article we propose using the LLR test — a longitudinal extension of the log-rank test statistic given by Peto and Peto (1972) — to provide evidence of a plausible association between a time-to-event outcome (right- or interval-censored) and a time-dependent covariate. As joint model methods ...
Citation
Oller, R.; Gómez Melis, G. A nonparametric test for the association between longitudinal covariates and censored survival data. "Biostatistics", 1 Octubre 2020, vol. 21, núm. 4, p. 727-742.
Keywords
Interval-censored data, Log-rank test, Longitudinal data analysis, Nonparametric maximum likelihood estimator, Per-mutation test, Right-censored data
Group of research
GRBIO - Biostatistics and Bioinformatics Research Group

Participants