Sequential Multiple Assignment Randomized Trials Design and Analyses

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Documentation for package ‘rsmart’ version 0.1.0

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

Help Pages

block_rand	Create a blocked randomization function
estimate_values	Estimate values for all treatment regimes
gen_no_trt_resp	Generate sample data for a two-stage SMART where responders are not re-randomized
get_an	Compute the An matrix for the sandwich variance estimator
get_bn	Compute the Bn matrix for the sandwich variance estimator
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_kappa	Compute the kappa (stage reached) for each individual
get_next_bound	Compute subsequent stopping boundaries for a group sequential design
get_nu	Estimate stage arrival probabilities (nu)
get_q_coefs	Extract coefficients from all fitted Q-function models
get_q_fits	Fit outcome regression (Q-function) models across all stages for a single regime
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
iaipwe	IAIPWE for K-stage SMARTs with up to 2 treatment options at each stage
pcsttrial	pcsttrial: Simulated Clinical Trial Data for Pain Coping Skills Training
pi_fits	Fit propensity score models for all stages
pstep	Fit a propensity score model for a single stage
qstep	Fit an outcome regression (Q-function) model for a single stage
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
smart_design	Compute stopping boundaries and sample size for a group sequential SMART
value_terms	Compute the individual-level value terms for a single regime