Return a message that contains the estimated strategy-specified means and their confidence interval, as well as the asymptotic variance-covariance matrix for these estimates.
smartsize(
sim = NULL,
delta = NULL,
df = NULL,
alpha = 0.05,
beta = 0.2,
global = TRUE,
family = c("gaussian", "binomial")[1]
)A numeric matrix containing the values of treatment sequence-specific parameters to generate the SMART data, including the values of stage-specific treatments, intermediate outcome and final primary outcome.
The standardized effect size for sample size calculation.
The degrees of freedom for the chisquare test.
Type I error rate.
Type II error rate.
If TRUE then power the SMART based on a global test, otherwise power the SMART based on a pairwise test. The default is TRUE
A character string to specify the type of final primary outcome. The default is family=<U+201C>gaussian<U+201D>, which refers to the continuous primary outcome. If family=<U+201D>binomial<U+201D> then the primary outcome will be treated as binary variable.
Standardized effect size and total sample size for SMART
delta: standardized effect size
n: total sample size
Murphy, S. A. (2005). An experimental design for the development of adaptive treatment strategies. Statistics in Medicine. 24(10): 1455-1481.
Ogbagaber S. B., Karp, J., and Wahed A.S. (2015). Design of sequentially randomization trials for testing adaptive treatment strategies. Statistics in Medicine. DOI: 10.1002/sim.6747.