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Data from: A novel nonparametric measure of explained variation for survival data with an easy graphical interpretation

Citation

Weiß, Verena; Schmidt, Matthias; Hellmich, Martin (2015), Data from: A novel nonparametric measure of explained variation for survival data with an easy graphical interpretation, Dryad, Dataset, https://doi.org/10.5061/dryad.5c6bq

Abstract

Introduction: For survival data the coefficient of determination cannot be used to describe how good a model fits to the data. Therefore, several measures of explained variation for survival data have been proposed in recent years. Methods: We analyse an existing measure of explained variation with regard to minimisation aspects and demonstrate that these are not fulfilled for the measure. Results: In analogy to the least squares method from linear regression analysis we develop a novel measure for categorical covariates which is based only on the Kaplan-Meier estimator. Hence, the novel measure is a completely nonparametric measure with an easy graphical interpretation. For the novel measure different weighting possibilities are available and a statistical test of significance can be performed. Eventually, we apply the novel measure and further measures of explained variation to a dataset comprising persons with a histopathological papillary thyroid carcinoma. Conclusion: We propose a novel measure of explained variation with a comprehensible derivation as well as a graphical interpretation, which may be used in further analyses with survival data.

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