| des_dtl_bern | R Documentation | 
des_dtl_bern() determines multi-stage drop-the-losers multi-arm
clinical trial designs assuming the primary outcome variable is Bernoulli
distributed. It computes required design components and returns information
on key operating characteristics.
des_dtl_bern(
  Kv = c(2, 1),
  alpha = 0.025,
  beta = 0.1,
  pi0 = 0.3,
  delta1 = 0.2,
  delta0 = 0,
  ratio = 1,
  power = "marginal",
  type = "variable",
  spacing = (1:length(Kv))/length(Kv),
  integer = F,
  summary = F
)
| Kv | A  | 
| alpha | A  | 
| beta | A  | 
| pi0 | A  | 
| delta1 | A  | 
| delta0 | A  | 
| ratio | A  | 
| power | A  | 
| type | A  | 
| spacing | A  | 
| integer | A  | 
| summary | A  | 
A list, with additional class
"multiarm_des_dtl_bern", containing the following elements:
 A tibble in the slot $opchar summarising the
operating characteristics of the identified design.
 A numeric in the slot $e specifying
e, the trial's critical rejection
boundary for the final analysis.
 A numeric in the slot $maxN specifying
N, the trial's total required sample
size.
 A numeric in the slot $n_factor, for internal use
in other functions.
 A numeric in the slot $n1 specifying
n1, the total sample size
required in stage one of the trial.
 A numeric in the slot $n10 specifying
n10, the sample size
required in the control arm in stage one of the trial.
Each of the input variables.
build_dtl_bern, gui,
opchar_dtl_bern, plot.multiarm_des_dtl_bern,
sim_dtl_bern.
# The design for the default parameters
des <- des_dtl_bern()
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