AutoScore_fine_tuning   AutoScore STEP(iv): Fine-tune the score by
                        revising cut_vec with domain knowledge
                        (AutoScore Module 5)
AutoScore_fine_tuning_Ordinal
                        AutoScore STEP(iv) for ordinal outcomes:
                        Fine-tune the score by revising 'cut_vec' with
                        domain knowledge (AutoScore Module 5)
AutoScore_fine_tuning_Survival
                        AutoScore STEP(iv) for survival outcomes:
                        Fine-tune the score by revising cut_vec with
                        domain knowledge (AutoScore Module 5)
AutoScore_impute        Internal function: impute missing values in the
                        training and validation sets
AutoScore_parsimony     AutoScore STEP(ii): Select the best model with
                        parsimony plot (AutoScore Modules 2+3+4)
AutoScore_parsimony_Ordinal
                        AutoScore STEP(ii) for ordinal outcomes: Select
                        the best model with parsimony plot (AutoScore
                        Modules 2+3+4)
AutoScore_parsimony_Survival
                        AutoScore STEP(ii) for survival outcomes:
                        Select the best model with parsimony plot
                        (AutoScore Modules 2+3+4)
AutoScore_rank          AutoScore STEP(i): Rank variables with machine
                        learning (AutoScore Module 1)
AutoScore_rank_Ordinal
                        AutoScore STEP (i) for ordinal outcomes:
                        Generate variable ranking list by machine
                        learning (AutoScore Module 1)
AutoScore_rank_Survival
                        AutoScore STEP (1) for survival outcomes:
                        Generate variable ranking List by machine
                        learning (Random Survival Forest) (AutoScore
                        Module 1)
AutoScore_testing       AutoScore STEP(v): Evaluate the final score
                        with ROC analysis (AutoScore Module 6)
AutoScore_testing_Ordinal
                        AutoScore STEP(v) for ordinal outcomes:
                        Evaluate the final score (AutoScore Module 6)
AutoScore_testing_Survival
                        AutoScore STEP(v) for survival outcomes:
                        Evaluate the final score with ROC analysis
                        (AutoScore Module 6)
AutoScore_weighting     AutoScore STEP(iii): Generate the initial score
                        with the final list of variables (Re-run
                        AutoScore Modules 2+3)
AutoScore_weighting_Ordinal
                        AutoScore STEP(iii) for ordinal outcomes:
                        Generate the initial score with the final list
                        of variables (Re-run AutoScore Modules 2+3)
AutoScore_weighting_Survival
                        AutoScore STEP(iii) for survival outcomes:
                        Generate the initial score with the final list
                        of variables (Re-run AutoScore Modules 2+3)
add_baseline            Internal Function: Add baselines after
                        second-step logistic regression (part of
                        AutoScore Module 3)
assign_score            Internal Function: Automatically assign scores
                        to each subjects given new data set and scoring
                        table (Used for intermediate and final
                        evaluation)
bca                     Bias-corrected and accelerated confidence
                        intervals
change_reference        Internal Function: Change Reference category
                        after first-step logistic regression (part of
                        AutoScore Module 3)
check_data              AutoScore function for datasets with binary
                        outcomes: Check whether the input dataset
                        fulfill the requirement of the AutoScore
check_data_ordinal      AutoScore function for ordinal outcomes: Check
                        whether the input dataset fulfil the
                        requirement of the AutoScore
check_data_survival     AutoScore function for survival data: Check
                        whether the input dataset fulfill the
                        requirement of the AutoScore
check_link              Internal function: Check link function
check_predictor         Internal function: Check predictors
compute_auc_val         Internal function: Compute AUC based on
                        validation set for plotting parsimony
                        (AutoScore Module 4)
compute_auc_val_ord     Internal function: Compute mean AUC for ordinal
                        outcomes based on validation set for plotting
                        parsimony
compute_auc_val_survival
                        Internal function for survival outcomes:
                        Compute AUC based on validation set for
                        plotting parsimony
compute_descriptive_table
                        AutoScore function: Descriptive Analysis
compute_final_score_ord
                        Internal function: Compute risk scores for
                        ordinal data given variables selected, cut-off
                        values and scoring table
compute_mauc_ord        Internal function: Compute mAUC for ordinal
                        predictions
compute_multi_variable_table
                        AutoScore function: Multivariate Analysis
compute_multi_variable_table_ordinal
                        AutoScore-Ordinal function: Multivariate
                        Analysis
compute_multi_variable_table_survival
                        AutoScore function for survival outcomes:
                        Multivariate Analysis
compute_prob_observed   Internal function: Based on given labels and
                        scores, compute proportion of subjects observed
                        in each outcome category in given score
                        intervals.
compute_prob_predicted
                        Internal function: Based on given labels and
                        scores, compute average predicted risks in
                        given score intervals.
compute_score_table     Internal function: Compute scoring table based
                        on training dataset (AutoScore Module 3)
compute_score_table_ord
                        Internal function: Compute scoring table for
                        ordinal outcomes based on training dataset
compute_score_table_survival
                        Internal function: Compute scoring table for
                        survival outcomes based on training dataset
compute_uni_variable_table
                        AutoScore function: Univariable Analysis
compute_uni_variable_table_ordinal
                        AutoScore-Ordinal function: Univariable
                        Analysis
compute_uni_variable_table_survival
                        AutoScore function for survival outcomes:
                        Univariate Analysis
conversion_table        AutoScore function: Print conversion table
                        based on final performance evaluation
conversion_table_ordinal
                        AutoScore function: Print conversion table for
                        ordinal outcomes to map score to risk
conversion_table_survival
                        AutoScore function for survival outcomes: Print
                        conversion table
estimate_p_mat          Internal function: generate probability matrix
                        for ordinal outcomes given thresholds, linear
                        predictor and link function
eva_performance_iauc    Internal function survival outcome: Calculate
                        iAUC for validation set
evaluate_model_ord      Internal function: Evaluate model performance
                        on ordinal data
extract_or_ci_ord       Extract OR, CI and p-value from a proportional
                        odds model
find_one_inds           Internal function: Find column indices in
                        design matrix that should be 1
find_possible_scores    Internal function: Compute all scores
                        attainable.
get_cut_vec             Internal function: Calculate cut_vec from the
                        training set (AutoScore Module 2)
group_score             Internal function: Group scores based on given
                        score breaks, and use friendly names for first
                        and last intervals.
induce_informative_missing
                        Internal function: induce informative missing
                        to sample data in the package to demonstrate
                        how AutoScore handles missing as a separate
                        category
induce_median_missing   Internal function: induce informative missing
                        in a single variable
inv_cloglog             Internal function: Inverse cloglog link
inv_logit               Internal function: Inverse logit link
inv_probit              Internal function: Inverse probit link
make_design_mat         Internal function: Based on 'find_one_inds',
                        make a design matrix to compute all scores
                        attainable.
plot_auc                Internal function: Make parsimony plot
plot_importance         Internal Function: Print plotted variable
                        importance
plot_predicted_risk     AutoScore function for binary and ordinal
                        outcomes: Plot predicted risk
plot_roc_curve          Internal Function: Plotting ROC curve
plot_survival_km        AutoScore function for survival outcomes: Print
                        scoring performance (KM curve)
print_performance_ci_survival
                        AutoScore function for survival outcomes: Print
                        predictive performance with confidence
                        intervals
print_performance_ordinal
                        AutoScore function for ordinal outcomes: Print
                        predictive performance
print_performance_survival
                        AutoScore function for survival outcomes: Print
                        predictive performance
print_roc_performance   AutoScore function: Print receiver operating
                        characteristic (ROC) performance
print_scoring_table     AutoScore Function: Print scoring tables for
                        visualization
sample_data             20000 simulated ICU admission data, with the
                        same distribution as the data in the MIMIC-III
                        ICU database
sample_data_ordinal     Simulated ED data with ordinal outcome
sample_data_ordinal_small
                        Simulated ED data with ordinal outcome (small
                        sample size)
sample_data_small       1000 simulated ICU admission data, with the
                        same distribution as the data in the MIMIC-III
                        ICU database
sample_data_survival    20000 simulated MIMIC sample data with survival
                        outcomes
sample_data_survival_small
                        1000 simulated MIMIC sample data with survival
                        outcomes
sample_data_with_missing
                        20000 simulated ICU admission data with missing
                        values
split_data              AutoScore Function: Automatically splitting
                        dataset to train, validation and test set,
                        possibly stratified by label
transform_df_fixed      Internal function: Categorizing continuous
                        variables based on cut_vec (AutoScore Module 2)
