Figure 3:
The proposed adaptive splitting approach provides a good compromise between predictive performance and the statistical power of the external validation. The left and right column show the comparison of splitting methods on external validation performance and P-values, respectively, at various 
. Confidence intervals are based on 100 repetitions of the analyses. The adaptive splitting approach (blue) provides a good compromise between predictive performance and statistical power of the external validation. The Pareto split (red) provides similar external validation performances to adaptive splitting; however, it often fails to provide conclusive results due to an insufficient sample size during external validation, especially in case of a limited sample size budget. The 90%:10% split (green) provides only slightly higher performances than the Pareto and the adaptive splitting techniques, but it very often gives inconclusive results (
) in the external validation sample. Half-split (yellow) tends to provide worse predictive performance due to the too small discovery sample.