View source: R/plot.multiarm_des_ss_norm.R
| plot.multiarm_des_ss_norm | R Documentation | 
plot.multiarm_des_ss_norm() produces power curve plots for a specified
single-stage multi-arm clinical trial design assuming the primary outcome is
normally distributed.
## S3 method for class 'multiarm_des_ss_norm'
plot(
  x = des_ss_norm(),
  delta_min = -x$delta1,
  delta_max = 2 * x$delta1,
  delta = x$delta1 - x$delta0,
  density = 100,
  output = FALSE,
  print_plots = TRUE,
  summary = FALSE,
  ...
)
| x | A  | 
| delta_min | A  | 
| delta_max | A  | 
| delta | A  | 
| density | A  | 
| output | A  | 
| print_plots | A  | 
| summary | A  | 
| ... | Not currently used. | 
If output = T, a list containing the following elements
 A list in the slot $plots containing the produced
plots.
Each of the input variables.
build_ss_norm, des_ss_norm,
gui, opchar_ss_norm, sim_ss_norm.
## Not run: 
# The design for the default parameters
des        <- des_ss_norm()
plot(des)
# An A-optimal design, returning the avaiable outputs from
# plot.multiarm_des_ss_norm()
des_A      <- des_ss_norm(ratio = "A")
plots      <- plot(des_A, output = T)
# Using the root-K allocation rule, modifying the desired type of power, and
# choosing an alternative multiple comparison correction
des_root_K <- des_ss_norm(ratio      = rep(1/sqrt(2), 2),
                          correction = "holm_bonferroni",
                          power      = "disjunctive")
plot(des_root_K)
## End(Not run)
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