Performance Assessment for Continuous and Survival Outcomes

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Documentation for package ‘PAmeasures’ version 2.0.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

moore	Moore's Law Data
pam.nlm	Prediction Accuracy for Continuous Outcomes
pa_calibration	Calibration of Predicted Event Probabilities at One Time Point
pa_calibration_cr	Calibration of Predicted Event Probabilities at One Time Point
pa_case_cohort_weights	Case-cohort sampling weights
pa_evaluate_two_phase	Evaluate Survival Model Metrics for Two-Phase Sampling Designs
pa_fit_and_eval	Performance Metrics for Survival Analysis Models
pa_metric_names	Canonical metric names
pa_nested_case_control_weights	Nested case-control (NCC) sampling weights
pa_nlm	Prediction Accuracy for Continuous Outcomes
pa_plot_pred	Quick Diagnostic Plot for Survival Model Predicted Probabilities
pa_plot_summary	Arrange multiple prediction plots with letter tags
pa_predict_cif	Predict Subject-Specific Cumulative Incidence Function (CIF)
pa_predict_coxph	Prediction Accuracy Measures for Cox Proportional Hazards Model
pa_predict_survreg	Prediction Accuracy Measures for Parametric Survival Regression Models
pa_sample_design	Summarize multiple two-phase (case-cohort) models into a wide table
pa_simulate_fine_gray	Simulate data from a two-cause Fine-Gray model
pa_sim_cox_weibull	Simulate Cox survival data with optional interaction terms and targeted censoring
pa_summarize	Summarize multiple survival models into a wide comparison table
pa_summarize_cr	Summarize multiple competing-risks models into a wide comparison table
pa_survival_eval	Compute Survival Model Evaluation Metrics
pa_survival_eval_cr	Evaluate Survival Prediction Performance with Competing Risks