Statistical Combination of Diagnostic Tests

Documentation for package ‘dtComb’ version 1.0.6

Help Pages

dtComb-package	dtComb: A Comprehensive R Package for Combining Diagnostic Tests
allMethods	Machine learning model table for mlComb() Includes machine learning models used for the mlComb function
availableMethods	Available classification/regression methods in 'dtComb'
dtComb	dtComb: A Comprehensive R Package for Combining Diagnostic Tests
exampleData2	Biomarker data from carriers of a rare genetic disorder A data set containing the carriers of a rare genetic disorder for 120 samples.
exampleData3	Simulated data with healthy and diseased individuals A simulation data containing 250 diseased and 250 healthy individuals.
helper_minimax	Helper function for minimax method.
helper_minmax	Helper function for minmax method.
helper_PCL	Helper function for PCL method.
helper_PT	Helper function for PT method.
helper_TS	Helper function for TS method.
kappa.accuracy	Calculate Cohen's kappa and accuracy.
laparotomy	Diagnostic laparotomy dataset A data set containing the results of diagnostic laparotomy procedures for 225 patients.
linComb	Linear Combination Methods for Diagnostic Test Scores
mathComb	Combine two diagnostic tests with several mathematical operators and distance measures.
mlComb	Combine two diagnostic tests with Machine Learning Algorithms.
nonlinComb	Combine two diagnostic tests with several non-linear combination methods.
plotComb	Plot the combination scores using the training model
predict.dtComb	Predict combination scores and labels for new data sets using the training model
print_train	Print the summary of linComb, nonlinComb, mlComb and mathComb functions.
rocsum	Generate ROC curves and related statistics for the given markers and Combination score.
std.test	Standardization according to the training model parameters.
std.train	Standardization according to the chosen method.
transform_math	Mathematical transformations for biomarkers