| ThresholdROCsurvival-package {ThresholdROCsurvival} | R Documentation |
Diagnostic Ability Assessment with Right-Censored Data at a Fixed Time t
Description
We focus on the diagnostic ability assessment of medical tests when the outcome of interest is the status (alive or dead) of the subjects at a certain time-point t. This binary status is determined by right-censored times to event and it is unknown for those subjects censored before t. Here we provide three methods (unknown status exclusion, imputation of censored times and using time-dependent ROC curves) to evaluate the diagnostic ability of binary and continuous tests in this context. Two references for the methods used here are Skaltsa et al. (2010) <doi:10.1002/bimj.200900294> and Heagerty et al. (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.
Details
The functions in this package are diagnostic_assessment_binary() (for binary medical tests) and diagnostic_assessment_continuous() (for continuous medical tests).
Author(s)
Sara Perez-Jaume and Josep L Carrasco
Maintainer: Sara Perez-Jaume
References
Heagerty PJ, Lumley T, Pepe MS. Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker. Biometrics 2000; 56(2): 337-344. doi: 10.1111/j.0006-341X.2000.00337.x
Hsu CH, Taylor JMG, Murray S, Commenges D. Survival analysis using auxiliary variables via non-parametric multiple imputation. Statistics in Medicine 2006; 25(20): 3503-3517. doi: https://doi.org/10.1002/sim.2452
Perez-Jaume S, Skaltsa K, Pallares N, Carrasco JL. ThresholdROC: Optimum Threshold Estimation Tools for Continuous Diagnostic Tests in R. Journal of Statistical Software 2017; 82(4): 1-21. doi: 10.18637/jss.v082.i04
Skaltsa K, Jover L, Carrasco JL. Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty. Biometrical Journal 2010; 52(5): 676-697. doi: 10.1002/bimj.200900294