optimal_normal_generic: Generic function for optimizing normally distributed...

In Sterniii3/drugdevelopR: Utility-Based Optimal Phase II/III Drug Development Planning

Generic function for optimizing normally distributed endpoints

Description

Generic function for optimizing normally distributed endpoints

Usage

optimal_normal_generic(
  w,
  Delta1,
  Delta2,
  in1,
  in2,
  a,
  b,
  n2min,
  n2max,
  stepn2,
  kappamin,
  kappamax,
  stepkappa,
  alpha,
  beta,
  c2,
  c3,
  c02,
  c03,
  K = Inf,
  N = Inf,
  S = -Inf,
  steps1 = 0,
  stepm1 = 0.5,
  stepl1 = 0.8,
  b1,
  b2,
  b3,
  gamma = 0,
  fixed = FALSE,
  num_cl = 1
)

Arguments

w	weight for mixture prior distribution
Delta1	assumed true prior treatment effect measured as the standardized difference in means, see here for details
Delta2	assumed true prior treatment effect measured as the standardized difference in means, see here for details
in1	amount of information for Delta1 in terms of sample size, see here for details
in2	amount of information for Delta2 in terms of sample size, see here for details
a	lower boundary for the truncation of the prior distribution
b	upper boundary for the truncation of the prior distribution
n2min	minimal total sample size for phase II; must be an even number
n2max	maximal total sample size for phase II, must be an even number
stepn2	step size for the optimization over n2; must be an even number
kappamin	minimal threshold value kappa for the go/no-go decision rule
kappamax	maximal threshold value kappa for the go/no-go decision rule
stepkappa	step size for the optimization over the threshold value kappa
alpha	one-sided significance level
beta	type II error rate; i.e. 1 - beta is the power for calculation of the sample size for phase III
c2	variable per-patient cost for phase II in 10^5 $
c3	variable per-patient cost for phase III in 10^5 $
c02	fixed cost for phase II in 10^5 $
c03	fixed cost for phase III in 10^5 $
K	constraint on the costs of the program, default: Inf, e.g. no constraint
N	constraint on the total expected sample size of the program, default: Inf, e.g. no constraint
S	constraint on the expected probability of a successful program, default: -Inf, e.g. no constraint
steps1	lower boundary for effect size category "small", default: 0
stepm1	lower boundary for effect size category "medium" = upper boundary for effect size category "small" default: 0.5
stepl1	lower boundary for effect size category "large" = upper boundary for effect size category "medium", default: 0.8
b1	expected gain for effect size category "small" in 10^5 $
b2	expected gain for effect size category "medium" in 10^5 $
b3	expected gain for effect size category "large" in 10^5 $
gamma	to model different populations in phase II and III choose gamma != 0, default: 0, see here for details
fixed	choose if true treatment effects are fixed or following a prior distribution, if TRUE Delta1 is used as fixed effect
num_cl	number of clusters used for parallel computing, default: 1

Sterniii3/drugdevelopR documentation built on Jan. 26, 2024, 6:17 a.m.