Spearman-like correlation measure adjusting for covariates in bivariate survival data.

ABSTRACT: We propose an extension of Spearman's correlation for censored continuous and discrete data that permits covariate adjustment. Previously proposed nonparametric and semiparametric Spearman's correlation estimators require either nonparametric estimation of the bivariate survival surface or parametric assumptions about the dependence structure. In practice, nonparametric estimation of the bivariate survival surface is difficult, and parametric assumptions about the correlation structure may not be satisfied. Therefore, we propose a method that requires neither and uses only the marginal survival distributions. Our method estimates the correlation of probability-scale residuals, which has been shown to equal Spearman's correlation when there is no censoring. Because this method relies only o

SUBMITTER: Eden SK 

PROVIDER: S-EPMC10897866 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature