The analysis of correlations within pairs of failure times is of interest to many research topics in medicine, such as the correlation of survival-type endpoints of twins, the correlation of times till failure in paired organs, or the correlation of survival time with a surrogate endpoint. The dependence of such times is assumed monotonic, and thus quantification by nonparametric correlation coefficients is appropriate. The typical censoring of such times requires more involved methods of statistical analysis. The SAS macro SURVCORR and the R package SurvCorr produce point and interval estimates of Spearman's rS under possible censoring of both failure times, assuming a normal copula for the bivariate failure distribution and by implementing a novel iterative multiple imputation algorithm. This method provides an interesting alternative to implementations of maximum likelihood methodology for the normal copula approach, reducing computing time to about 0.2% without sacrificing statistical performance. For iterative multiple imputation, survival probabilities at death or censoring times are first transformed to normal deviates. Then, those deviates which relate to censored times are iteratively augmented, by conditional multiple imputation, until convergence is obtained for Spearman's rS. The algorithm is presented in detail by Schemper et al (2013).
Referenzen:
Schemper,M., Kaider,A., Wakounig,S. & Heinze,G. (2013): "Estimating the correlation of bivariate failure times under censoring", Statistics in Medicine, 32, 4781-4790 (doi:10.1002/sim.5874).
Das R-package SurvCorr ist auf dem CRAN erhältlich.
Die derzeitige Version des SAS-Makros verwendet ein MS-DOS-Programm, das eine IMSL-Installation voraussetzt. An einer IMSL-unabhängigen Version wird gearbeitet.
Unser Programm steht Ihnen kostenlos zur Verfügung. Wir bitten Sie jedoch, Ihren Namen und Ihre Mailadresse anzugeben; wir benachrichtigen Sie, wenn es eine neue Version zum Download gibt:
| SURVCORR | |
Name: | |
| E-Mail-Adresse: | |