| dtComb-package | dtComb: A Comprehensive R Library for Combining Diagnostic Tests |
| allMethods | Includes machine learning models used for the mlComb function |
| availableMethods | Available classification/regression methods in 'dtComb' |
| dtComb | dtComb: A Comprehensive R Library for Combining Diagnostic Tests |
| exampleData1 | Examples data for the dtComb package |
| exampleData2 | A data set containing the carriers of a rare genetic disorder for 120 samples. |
| exampleData3 | 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. |
| linComb | Combine two diagnostic tests with several linear combination methods. |
| 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. |