Statistical Combination of Diagnostic Tests

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Documentation for package ‘dtComb’ version 1.0.7

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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