powerCal {riskPredictClustData} | R Documentation |
Calculate the power for testing \delta=0
Description
Calculate the power for testing \delta=0
.
Usage
powerCal(
nSubj,
mu1,
triangle,
rho,
rho11,
rho22,
rho12,
p11,
p10,
p01,
alpha = 0.05)
Arguments
nSubj |
integer. number of subjects to be generated. Assume each subject has two observations. |
mu1 |
|
triangle |
the difference of the expected value the the extended Mann-Whitney U statistics
between two prediction rules, i.e., |
rho |
|
rho11 |
|
rho22 |
|
rho12 |
|
p11 |
|
p10 |
|
p01 |
|
alpha |
type I error rate |
Value
the power
Author(s)
Bernard Rosner <stbar@channing.harvard.edu>, Weiliang Qiu <Weiliang.Qiu@gmail.com>, Meiling Ting Lee <MLTLEE@umd.edu>
References
Rosner B, Qiu W, and Lee MLT. Assessing Discrimination of Risk Prediction Rules in a Clustered Data Setting. Lifetime Data Anal. 2013 Apr; 19(2): 242-256.
Examples
set.seed(1234567)
mu1 = 0.8
power = powerCal(nSubj = 30, mu1 = mu1,
triangle = 0.05, rho = 0.93, rho11 = 0.59, rho22 = 0.56, rho12 = 0.52,
p11 = 0.115, p10 = 0.142, p01 = 0.130, alpha = 0.05)
print(power)