utility23_binary {drugdevelopR} | R Documentation |
Utility function for multitrial programs deciding between two or three phase III trials for a binary distributed outcome
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 further step maximized by the optimal_multitrial_binary()
function.
Usage
utility23_binary(
n2,
RRgo,
w,
p0,
p11,
p12,
in1,
in2,
alpha,
beta,
c2,
c3,
c02,
c03,
b1,
b2,
b3
)
Arguments
n2 |
total sample size for phase II; must be even number |
RRgo |
threshold value for the go/no-go decision rule |
w |
weight for mixture prior distribution |
p0 |
assumed true rate of control group |
p11 |
assumed true rate of treatment group |
p12 |
assumed true rate of treatment group |
in1 |
amount of information for |
in2 |
amount of information for |
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 |
Value
The output of the function utility23_binary()
is the expected utility of the program depending on whether two or three phase III trials are performed.
Examples
utility23_binary(n2 = 50, RRgo = 0.8, w = 0.3,
alpha = 0.05, beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
in1 = 300, in2 = 600,
c2 = 0.75, c3 = 1, c02 = 100, c03 = 150,
b1 = 1000, b2 = 2000, b3 = 3000)