View source: R/functions_multitrial.R
utility23 | 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 further step maximized by the optimal_multitrial()
function.
utility23(
d2,
HRgo,
w,
hr1,
hr2,
id1,
id2,
alpha,
beta,
xi2,
xi3,
c2,
c3,
c02,
c03,
b1,
b2,
b3
)
d2 |
total sample size for phase II; must be even number |
HRgo |
threshold value for the go/no-go decision rule |
w |
weight for mixture prior distribution |
hr1 |
first assumed true treatment effect on HR scale for prior distribution |
hr2 |
second assumed true treatment effect on HR scale for prior distribution |
id1 |
amount of information for |
id2 |
amount of information for |
alpha |
significance level |
beta |
|
xi2 |
event rate for phase II |
xi3 |
event rate for phase III |
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()
is the expected utility of the program depending on whether two or three phase III trials are performed.
utility23(d2 = 50, HRgo = 0.8, w = 0.3,
hr1 = 0.69, hr2 = 0.81,
id1 = 280, id2 = 420,
alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
b1 = 1000, b2 = 2000, b3 = 3000)
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