A simulation study of predictive ability measures in a survival model II: explained randomness and predictive accuracy

Stat Med. 2012 Oct 15;31(23):2644-59. doi: 10.1002/sim.5460. Epub 2012 Jul 5.

Abstract

Several R(2) -type measures have been proposed to evaluate the predictive ability of a survival model. In Part I, we classified the measures into four categories and studied the measures in the explained variation category. In this paper, we study the remaining measures in a similar fashion, discussing their strengths and shortcomings. Simulation studies are used to examine the performance of the measures with respect to the criteria we set out in Part I. Our simulation studies showed that among the measures studied in this paper, the measures proposed by Kent and O'Quigley ρ(W)(2) (and its approximation ρ(W,A)(2)) and Schemper and Kaider R(SK)(2) perform better with respect to our criteria. However, our investigations showed that ρ(W)(2) is adversely affected by the distribution of covariate and the presence of influential observations. The results show that the other measures perform poorly, primarily because they are affected either by the degree of censoring or the follow-up period.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / pathology
  • Disease-Free Survival
  • Female
  • Humans
  • Leg Ulcer / pathology
  • Lymphoma, Large B-Cell, Diffuse / pathology
  • Models, Statistical*
  • Predictive Value of Tests*
  • Prognosis*
  • Reproducibility of Results
  • Survival Analysis*
  • Wound Healing / physiology