ArticleBiometrics2022
Nonparametric estimation of Spearman's rank correlation with bivariate survival data.
Article in Biometrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Trial
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- [Comment on the article "Workplace violence as a predictor of suicidal ideation in undergraduate internal physicians"].Revista medica del Instituto Mexicano del Seguro Social · 2026Article
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- Integration of multi-omics profiling reveals an epigenetic-based molecular classification of lung adenocarcinoma: implications for drug sensitivity and immunotherapy response prediction.Frontiers in pharmacology · 2025Article
- Correlation between structural determinants and universal health coverage in 2010 and 2019: An analysis of the global burden of disease study.PLOS global public health · 2025Article
- Unveiling shared therapeutic targets and pathological pathways between coronary artery disease and major depressive disorder through bioinformatics analysis.Scientific reports · 2024Article
- Deep learning for oncologic treatment outcomes and endpoints evaluation from CT scans in liver cancer.NPJ precision oncology · 2024Article
- A paradigm shift in cancer research based on integrative multi-omics approaches: glutaminase serves as a pioneering cuproptosis-related gene in pan-cancer.BMC women's health · 2024Article
- Spearman-like correlation measure adjusting for covariates in bivariate survival data.Biometrical journal. Biometrische Zeitschrift · 2023Article
- Prognostic value ofEJNMMI research · 2023Article
- Application of ensemble machine learning model in downscaling and projecting climate variables over different climate regions in Iran.Environmental science and pollution research international · 2022Article
- Pan-cancer analyses confirmed the cuproptosis-related gene FDX1 as an immunotherapy predictor and prognostic biomarker.Frontiers in genetics · 2022Article
- Observational
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Authors and funding
3 authors.
Funding
Abstract
We study rank-based approaches to estimate the correlation between two right-censored variables. With end-of-study censoring, it is often impossible to nonparametrically identify the complete bivariate survival distribution, and therefore it is impossible to nonparametrically compute Spearman's rank correlation. As a solution, we propose two measures that can be nonparametrically estimated. The first measure is Spearman's correlation in a restricted region. The second measure is Spearman's correlation for an altered but estimable joint distribution. We describe population parameters for these measures and illustrate how they are similar to and different from the overall Spearman's correlation. We propose consistent estimators of these measures and study their performance through simulations. We illustrate our methods with a study assessing the correlation between the time to viral failure and the time to regimen change among persons living with HIV in Latin America who start antiretroviral therapy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.