%0 DATA
%A Mariano, Rodriguez
%A M., Dolores Salmeron
%A Alejandro, Martin-Malo
%A Carlo, Barbieri
%A Flavio, Mari
%A Rafael, I. Molina
%A Pedro, Costa
%A Pedro, Aljama
%D 2016
%T Prediction error for Serum Phosphate concentration by each one of the variables included in the analysis.
%U https://plos.figshare.com/articles/figure/_Prediction_error_for_Serum_Phosphate_concentration_by_each_one_of_the_variables_included_in_the_analysis_/1642037
%R 10.1371/journal.pone.0146801.g004
%2 https://plos.figshare.com/ndownloader/files/2633896
%K rf
%K pth
%K kdigo
%K New Data Analysis System
%K data analysis system
%K mineral bone disease
%K phosphate
%K 1758 adult HD patients
%K correlation coefficient
%K variable
%K mineral metabolism parameters
%X The vertical axis of Fig 4 depicts the error in prediction of serum phosphate concentration (mg/dl) that will be caused if specific input variable is removed from the mathematical model generated by Random Forest. Sevelamer and calcium binders are positively associated with serum phosphate concentration because patients with hyperphosphatemia receive phosphate binders. The magnitude of prediction error obtained with each variable is being compared with the rest of the variables. Only variables that show a significant effect in predicting values of phosphate were included in this analysis.