Efficient Simulation-Based Power and Sample Size Calculations
for a Broad Class of Late-Stage Clinical Trials
Rcpp (>= 0.12.10), officer, flextable, devEMF, shiny,
shinydashboard, shinyMatrix
The following modules are included in the package:
Adaptive designs with data-driven sample size or event count re-estimation,
Adaptive designs with data-driven treatment selection,
Adaptive designs with data-driven population selection,
Optimal selection of a futility stopping rule,
Event prediction in event-driven trials.

Rcpp (>= 0.12.10), RcppEigen, RcppNumerical, officer,
flextable, devEMF, mvtnorm, shiny, shinydashboard, shinyMatrix

Rcpp (>= 0.12.10), RcppNumerical, officer, flextable, devEMF,
mvtnorm, shiny, shinydashboard, shinyMatrix
The following modules are included in the package:
Adaptive designs with data-driven sample size or event count re-estimation,
Adaptive designs with data-driven treatment selection,
Adaptive designs with data-driven population selection,
Optimal selection of a futility stopping rule,
Event prediction in event-driven trials.
Adaptive trials with response-adaptive randomization (experimental module).
Traditional trials with multiple objectives (experimental module).

The following modules are included in the package:
Adaptive designs with data-driven sample size or event count re-estimation,
Adaptive designs with data-driven treatment selection,
Adaptive designs with data-driven population selection,
Optimal selection of a futility stopping rule,
Event prediction in event-driven trials,
Adaptive trials with response-adaptive randomization (experimental module),
Traditional trials with multiple objectives (experimental module).

Rcpp (>= 0.12.10), RcppNumerical, officer, flextable, devEMF,
mvtnorm, shiny, shinydashboard, shinyMatrix, foreach, parallel,
doParallel, doRNG

The following modules are included in the package:
Adaptive designs with data-driven sample size or event count re-estimation,
Adaptive designs with data-driven treatment selection,
Adaptive designs with data-driven population selection,
Optimal selection of a futility stopping rule,
Event prediction in event-driven trials,
Adaptive trials with response-adaptive randomization (experimental module),
Traditional trials with multiple objectives (experimental module).
Traditional trials with cluster-randomized designs (experimental module).