R: Response-Adaptive Randomization in Clinical Trials

# Response-Adaptive Randomization in Clinical Trials

## Documentation for package ‘RARtrials’ version 0.0.2

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

## Help Pages

brar_select_au_binary | Select au in Bayesian Response-Adaptive Randomization with a Control Group for Binary Endpoint
brar_select_au_known_var | Select au in Bayesian Response-Adaptive Randomization with a Control Group for Continuous Endpoint with Known Variances
brar_select_au_unknown_var | Select au in Bayesian Response-Adaptive Randomization with a Control Group for Continuous Endpoint with Unknown Variances
convert_chisq_to_gamma | Convert parameters from a Normal-Inverse-Chi-Squared Distribution to a Normal-Inverse-Gamma Distribution
convert_gamma_to_chisq | Convert parameters from a Normal-Inverse-Gamma Distribution to a Normal-Inverse-Chi-Squared Distribution
dabcd_max_power | Allocation Probabilities Using Doubly Adaptive Biased Coin Design with Maximal Power Strategy for Binary Endpoint
dabcd_min_var | Allocation Probabilities Using Doubly Adaptive Biased Coin Design with Minimal Variance Strategy for Binary Endpoint
flgi_cut_off_binary | Cut-off Value of the Forward-looking Gittins Index Rule in Binary Endpoint
flgi_cut_off_known_var | Cut-off Value of the Forward-looking Gittins Index Rule in Continuous Endpoint with Known Variances
flgi_cut_off_unknown_var | Cut-off Value of the Forward-looking Gittins Index rule in Continuous Endpoint with Unknown Variances
Gittins | Gittins Indices
pgreater_beta | Calculate the Futility Stopping Probability for Binary Endpoint with Beta Distribution
pgreater_NIX | Calculate the Futility Stopping Probability for Continuous Endpoint with Unknown Variances Using a Normal-Inverse-Chi-Squared Distribution
pgreater_normal | Calculate the Futility Stopping Probability for Continuous Endpoint with Known Variances Using Normal Distribution
pmax_beta | Posterior Probability that a Particular Arm is the Best for Binary Endpoint
pmax_NIX | Posterior Probability that a Particular Arm is the Best for Continuous Endpoint with Unknown Variances
pmax_normal | Posterior Probability that a Particular Arm is the Best for Continuous Endpoint with Known Variances
sim_Aa_optimal_known_var | Simulate a Trial Using Aa-Optimal Allocation for Continuous Endpoint with Known Variances
sim_Aa_optimal_unknown_var | Simulate a Trial Using Aa-Optimal Allocation for Continuous Endpoint with Unknown Variances
sim_A_optimal_known_var | Simulate a Trial Using A-Optimal Allocation for Continuous Endpoint with Known Variances
sim_A_optimal_unknown_var | Simulate a Trial Using A-Optimal Allocation for Continuous Endpoint with Unknown Variances
sim_brar_binary | Simulate a Trial Using Bayesian Response-Adaptive Randomization with a Control Group for Binary Outcomes
sim_brar_known_var | Simulate a Trial Using Bayesian Response-Adaptive Randomization with a Control Group for Continuous Endpoint with Known Variances
sim_brar_unknown_var | Simulate a Trial Using Bayesian Response-Adaptive Randomization with a Control Group for Continuous Endpoint with Unknown Variances
sim_dabcd_max_power | Simulate a Trial Using Doubly Adaptive Biased Coin Design with Maximal Power Strategy for Binary Endpoint
sim_dabcd_min_var | Simulate a Trial Using Doubly Adaptive Biased Coin Design with Minmial Variance Strategy for Binary Endpoint
sim_flgi_binary | Simulate a Trial Using Forward-Looking Gittins Index for Binary Endpoint
sim_flgi_known_var | Simulate a Trial Using Forward-Looking Gittins Index for Continuous Endpoint with Known Variances
sim_flgi_unknown_var | Simulate a Trial Using Forward-Looking Gittins Index for Continuous Endpoint with Unknown Variances
sim_RPTW | Simulate a Trial Using Randomized Play-the-Winner Rule for Binary Endpoint
sim_RSIHR_optimal_known_var | Simulate a Trial Using Generalized RSIHR Allocation for Continuous Endpoint with Known Variances
sim_RSIHR_optimal_unknown_var | Simulate a Trial Using Generalized RSIHR Allocation for Continuous Endpoint with Unknown Variances
update_par_nichisq | Update Parameters of a Normal-Inverse-Chi-Squared Distribution with Available Data