R: Bayesian Sample Size and Precision Considerations for Risk Prediction Models

# Bayesian Sample Size and Precision Considerations for Risk Prediction Models

## Documentation for package ‘bayespmtools’ version 0.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

bpm_valprec | Bayesian Precision / VoI Calculator
bpm_valsamp | Bayesian Sample Size Calculator for External Validation
calc_ciw_2s | Calculates Pre-Posterior Distribution of 95% CI Widths Using Two-step Method
calc_ciw_mc | #'Calculates Pre-Posterior Distribution of 95% CI Widths Based on Given Method
calc_ciw_sample | Calculates Pre-Posterior Distribution of 95% CI Widths Using Sampling-based Simulation
calc_cstat | Calculates the C-statistic of Model
calc_riley_vars | Calculates Approximate Variances and Covariance for Performance Metrics
calc_se_sp | Calculates the Sensitivity and Specificity
find_n_mean | Calculates Sample Size Given Target Mean CI
find_n_quantile | Calculates Sample Size Given Target Quantile
infer_cal_int_from_mean | Infer Calibration Intercept from Mean Calibration
infer_cal_int_from_oe | Infer Calibration Intercept from O/E ratio
infer_correlation | Calculates Correlation
inv_mean_quantile | Calculates the Model Parameters Given Quantile
inv_moments | Calculates the Model Parameters Given Moments
isaric | Isaric Dataset
moments | Mean and Variance Calculator
plot_cal_distance | Plots Calibration Distance from Simulation Curves
plot_cal_instability | Plots Calibration Instability from Simulated Calibration Curves
process_evidence | Transforms Evidence Into Standardized Format
rbnorm | Generates Samples From Normal Distribution
riley_samp | Calculates Sample Size that Achieves Target CI Widths