predictionStats {FRESA.CAD}

Prediction Evaluation

Description

This function returns the statistical metrics describing the association between model predictions and the ground truth outcome

Usage

      predictionStats_binary(predictions, plotname="", center=FALSE,...)
      predictionStats_regression(predictions, plotname="",...)
      predictionStats_ordinal(predictions,plotname="",...)
      predictionStats_survival(predictions,plotname="",atriskthr=1.0,...)

Arguments

predictions

A matrix whose first column is the ground truth, and the second is the model prediction

plotname

The main title to be used by the plot function. If empty, no plot will be provided

center

For binary predictions indicates if the prediction is around zero

atriskthr

For survival predictions indicates the threshoold for at risk subjects.

...

Extra parameters to be passed to the plot function.

Details

These functions will analyze the prediction outputs and will compare to the ground truth. The output will depend on the prediction task: Binary classification, Linear Regression, Ordinal regression or Cox regression.

Value

accc

The classification accuracy with its95% confidence intervals (95/

berror

The balanced error rate with its 95%CI

aucs

The ROC area under the curve (ROC AUC) of the binary classifier with its 95%CI

specificity

The specificity with its 95%CI

sensitivity

The sensitivity with its 95%CI

ROC.analysis

The output of the ROC function

CM.analysis

The output of the epiR::epi.tests function

corci

the Pearson correlation with its 95%CI

biasci

the regression bias and its 95%CI

RMSEci

the root mean square error (RMSE) and its 95%CI

spearmanci

the Spearman correlation and its 95%CI

MAEci

the mean absolute difference(MAE) and its 95%CI

pearson

the output of the cor.test function

Kendall

the Kendall correlation and its 95%CI

Bias

the ordinal regression bias and its 95%CI

BMAE

the balanced mean absolute difference for ordinal regression

class95ci

the output of the bootstrapped estimation of accuracy, sensitivity, and ROC AUC

KendallTauB

the output of the DescTools::KendallTauB function

Kappa.analysis

the output of the irr::kappa2 function

CIFollowUp

The follow-up concordance index with its95% confidence intervals (95/

CIRisk

The risks concordance index with its95% confidence intervals (95/

LogRank

The LogRank test with its95% confidence intervals (95/

Author(s)

Jose G. Tamez-Pena

See Also

randomCV