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

Variable	RMSE: Training Set Using New Combined Quadratic Model	RMSE: Training Set Using Combined Logarithmic Model	Relative Reduction of RMSE for Training Set (%)	RMSE: Testing Set Using New Combined Quadratic Model	RMSE: Testing Set Using Combined Logarithmic Schwartz Model	Relative Reduction of RMSE for Testing Set (%)
Minimum	10.37	10.73	−0.83	9.76	09.93	−2.11
First quartile	11.70	12.21	3.23	12.05	12.46	1.94
Median	12.08	12.64	4.46	12.79	13.33	4.04
Mean	12.04	12.61	4.35	12.80	13.39	4.89
Third quartile	12.43	13.06	5.63	13.56	14.36	7.10
Maximum	13.29	13.98	10.40	16.68	17.59	14.24

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.