utility_multiple_normal {drugdevelopR} | R Documentation |
Utility function for multiple endpoints 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_multiple_normal()
function.
Usage
utility_multiple_normal(
kappa,
n2,
alpha,
beta,
Delta1,
Delta2,
in1,
in2,
sigma1,
sigma2,
c2,
c02,
c3,
c03,
K,
N,
S,
steps1,
stepm1,
stepl1,
b1,
b2,
b3,
fixed,
rho,
relaxed,
rsamp
)
Arguments
kappa |
threshold value for the go/no-go decision rule; vector for both endpoints |
n2 |
total sample size for phase II; must be even number |
alpha |
significance level |
beta |
|
Delta1 |
assumed true treatment effect given as difference in means for endpoint 1 |
Delta2 |
assumed true treatment effect given as difference in means for endpoint 2 |
in1 |
amount of information for |
in2 |
amount of information for |
sigma1 |
standard deviation of first endpoint |
sigma2 |
standard deviation of second endpoint |
c2 |
variable per-patient cost for phase II |
c02 |
fixed cost for phase II |
c3 |
variable per-patient cost for phase III |
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 |
steps1 |
lower boundary for effect size category |
stepm1 |
lower boundary for effect size category |
stepl1 |
lower boundary for effect size category |
b1 |
expected gain for effect size category |
b2 |
expected gain for effect size category |
b3 |
expected gain for effect size category |
fixed |
choose if true treatment effects are fixed or random, if TRUE |
rho |
correlation between the two endpoints |
relaxed |
relaxed or strict decision rule |
Value
The output of the function utility_multiple_normal()
is the expected utility of the program.