View source: R/functions_multitrial_normal.R
utility23_normal | R Documentation |
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.
utility23_normal(
n2,
kappa,
w,
Delta1,
Delta2,
in1,
in2,
a,
b,
alpha,
beta,
c2,
c3,
c02,
c03,
b1,
b2,
b3
)
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 |
b1 |
expected gain for effect size category |
b2 |
expected gain for effect size category |
b3 |
expected gain for effect size category |
The output of the function utility23_normal() is the expected utility of the program depending on whether two or three phase III trials are performed.
utility23_normal(n2 = 50, kappa = 0.2, w = 0.3, alpha = 0.025, beta = 0.1,
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,
b1 = 3000, b2 = 8000, b3 = 10000)
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