Table 4.

Root mean square error distribution in bootstrap samples using new combined serum creatinine and cystatin C quadratic model (232 degrees of freedom) and combined serum creatinine and cystatin C–based logarithmic Schwartz model (231 degrees of freedom) for both training and testing sets

VariableRMSE: Training Set Using New Combined Quadratic ModelRMSE: Training Set Using Combined Logarithmic ModelRelative Reduction of RMSE for Training Set (%)RMSE: Testing Set Using New Combined Quadratic ModelRMSE: Testing Set Using Combined Logarithmic Schwartz ModelRelative Reduction of RMSE for Testing Set (%)
Minimum10.3710.73−0.839.7609.93−2.11
First quartile11.7012.213.2312.0512.461.94
Median12.0812.644.4612.7913.334.04
Mean12.0412.614.3512.8013.394.89
Third quartile12.4313.065.6313.5614.367.10
Maximum13.2913.9810.4016.6817.5914.24
  • Relative reduction of RMSE was calculated by subtracting for each replicate the RMSE obtained from the combined logarithmic model and the one obtained from the combined quadratic model. RMSE, root mean square error.