Package index • rsmart

Primary Analysis

Main entry point for IAIPWE estimation

iaipwe(): IAIPWE for K-stage SMARTs with up to 2 treatment options at each stage
estimate_values(): Estimate values for all treatment regimes

Functions for SMART design, sample size, and stopping boundaries

smart_design(): Compute stopping boundaries and sample size for a group sequential SMART
get_sample_size(): Determine sample size for a group sequential SMART design
get_sample_size_chi(): Determine sample size for a chi-squared global test in a group sequential SMART design
get_bounds(): Compute all stopping boundaries for a two-analysis group sequential design
get_bounds_chi(): Compute the first chi-squared stopping boundary for a group sequential design
get_first_bound(): Compute the first stopping boundary for a group sequential design
get_next_bound(): Compute subsequent stopping boundaries for a group sequential design

Helpers for generating treatment regimes and simulating trials

gen_no_trt_resp(): Generate sample data for a two-stage SMART where responders are not re-randomized
regime_list_no_trt_resp(): Generate regime lists for a two-stage SMART where responders are not re-randomized
sim_treatment(): Simulate treatment assignments for a single stage
block_rand(): Create a blocked randomization function

Q-learning and propensity score model fitting

qstep(): Fit an outcome regression (Q-function) model for a single stage
pstep(): Fit a propensity score model for a single stage
get_q_fits(): Fit outcome regression (Q-function) models across all stages for a single regime
get_q_coefs(): Extract coefficients from all fitted Q-function models
pi_fits(): Fit propensity score models for all stages

Sandwich variance components

get_an(): Compute the An matrix for the sandwich variance estimator
get_bn(): Compute the Bn matrix for the sandwich variance estimator
value_terms(): Compute the individual-level value terms for a single regime
get_nu(): Estimate stage arrival probabilities (nu)
get_kappa(): Compute the kappa (stage reached) for each individual

Example datasets

pcsttrial: pcsttrial: Simulated Clinical Trial Data for Pain Coping Skills Training