Regression for Hierarchically Ordered Clinical Outcomes via
Pairwise Comparisons (Bradley-Terry-Davidson Model)
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Documentation for package ‘hpsreg’ version 1.0.0
Help Pages
| btd | Covariate-adjusted analysis of hierarchical pairwise outcomes |
| btd_calibration | Calibration of the pairwise model |
| btd_control | Control parameters for the Bradley-Terry-Davidson fit |
| btd_pair_probs | Predicted latent score and pair probabilities |
| hb_levels | Outcome levels for a hierarchy |
| hierarchy | Define a hierarchy of outcomes |
| hps_beta | Data-generating coefficients for the transplant example |
| hps_cox_grfs | Composite m-GRFS Cox model (comparator for the example) |
| hps_hierarchy | Hierarchy for the stem cell transplant example |
| lvl_binary | Outcome levels for a hierarchy |
| lvl_continuous | Outcome levels for a hierarchy |
| lvl_custom | Outcome levels for a hierarchy |
| lvl_group | Group several levels into one reporting level |
| lvl_ordinal | Outcome levels for a hierarchy |
| lvl_tte | Outcome levels for a hierarchy |
| openmp_threads | OpenMP availability |
| plot.btd_calibration | Plot a calibration table |
| predict.btd | Predicted latent score and pair probabilities |
| resolution | Where are pairs decided? |
| sample_pairs | Sample a random set of pairs |
| score_pairs | Score all pairs of subjects under a hierarchy |
| simulate_hps | Simulate a transplant cohort |
| summary.btd | Covariate-adjusted analysis of hierarchical pairwise outcomes |
| win_stats | Win statistics for two groups |