Choodari-Oskooei, B;
Royston, P;
Parmar, MKB;
(2015)
The extension of total gain (TG) statistic in survival models: Properties and applications.
BMC Medical Research Methodology
, 15
(1)
, Article 50. 10.1186/s12874-015-0042-x.
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Abstract
Background: The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R 2 -type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. Methods: In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). Results: The results of our simulations show that unlike many of the other R 2 -type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Conclusions: Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.
| Type: | Article |
|---|---|
| Title: | The extension of total gain (TG) statistic in survival models: Properties and applications |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s12874-015-0042-x |
| Publisher version: | https://doi.org/10.1186/s12874-015-0042-x |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Total gain, Predictive ability, Cox proportional hazards model, Non-proportional hazards, Time-dependent covariate |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1500500 |
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