utility_multitrial_normal {drugdevelopR} | R Documentation |
Utility function for multitrial programs with normally distributed outcomes
Description
The utility function calculates the expected utility of our drug development program and is given as gains minus costs and depends on the parameters and the expected probability of a successful program.
The utility is in a further step maximized by the optimal_multitrial_normal()
function.
Usage
utility2_normal(
n2,
kappa,
w,
Delta1,
Delta2,
in1,
in2,
a,
b,
alpha,
beta,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
utility3_normal(
n2,
kappa,
w,
Delta1,
Delta2,
in1,
in2,
a,
b,
alpha,
beta,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
utility4_normal(
n2,
kappa,
w,
Delta1,
Delta2,
in1,
in2,
a,
b,
alpha,
beta,
c2,
c3,
c02,
c03,
K,
N,
S,
b1,
b2,
b3,
case,
fixed
)
Arguments
n2 |
total sample size for phase II; must be even number |
kappa |
threshold value for the go/no-go decision rule |
w |
weight for mixture prior distribution |
Delta1 |
assumed true treatment effect for standardized difference in means |
Delta2 |
assumed true treatment effect for standardized difference in means |
in1 |
amount of information for |
in2 |
amount of information for |
a |
lower boundary for the truncation |
b |
upper boundary for the truncation |
alpha |
significance level |
beta |
|
c2 |
variable per-patient cost for phase II |
c3 |
variable per-patient cost for phase III |
c02 |
fixed cost for phase II |
c03 |
fixed cost for phase III |
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 |
b1 |
expected gain for effect size category |
b2 |
expected gain for effect size category |
b3 |
expected gain for effect size category |
case |
choose case: "at least 1, 2 or 3 significant trials needed for approval" |
fixed |
choose if true treatment effects are fixed or random |
Value
The output of the functions utility2_normal(), utility3_normal() and utility4_normal() is the expected utility of the program when 2, 3 or 4 phase III trials are performed.
Examples
res <- utility2_normal(kappa = 0.1, n2 = 50, alpha = 0.025, beta = 0.1, w = 0.3,
Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600,
a = 0.25, b = 0.75,
c2 = 0.675, c3 = 0.72, c02 = 15, c03 = 20,
K = Inf, N = Inf, S = -Inf,
b1 = 3000, b2 = 8000, b3 = 10000,
case = 2, fixed = TRUE)
res <- utility3_normal(kappa = 0.1, n2 = 50, alpha = 0.025, beta = 0.1, w = 0.3,
Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600,
a = 0.25, b = 0.75,
c2 = 0.675, c3 = 0.72, c02 = 15, c03 = 20,
K = Inf, N = Inf, S = -Inf,
b1 = 3000, b2 = 8000, b3 = 10000,
case = 2, fixed = TRUE)
res <- utility4_normal(kappa = 0.1, n2 = 50, alpha = 0.025, beta = 0.1, w = 0.3,
Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600,
a = 0.25, b = 0.75,
c2 = 0.675, c3 = 0.72, c02 = 15, c03 = 20,
K = Inf, N = Inf, S = -Inf,
b1 = 3000, b2 = 8000, b3 = 10000,
case = 3, fixed = TRUE)