simKHCE {hce} | R Documentation |
Simulate a kidney disease hce
dataset
Description
Simulate a kidney disease hce
dataset, capturing eGFR (Estimated Glomerular Filtration Rate) progression over time, along with
a competing and dependent terminal event: KFRT (Kidney Failure Replacement Therapy)
Usage
simKHCE(
n,
CM_A,
CM_P = -4,
n0 = n,
TTE_A = 10,
TTE_P = TTE_A,
fixedfy = 2,
Emin = 20,
Emax = 100,
sigma = 8,
Sigma = 3,
m = 10,
theta = -0.23,
phi = 0
)
Arguments
n |
sample size in the active treatment group. |
CM_A |
annualized eGFR slope in the active group. |
CM_P |
annualized eGFR slope in the control group. |
n0 |
sample size in the control treatment group. |
TTE_A |
event rate per year in the active group for KFRT. |
TTE_P |
event rate per year in the placebo group for KFRT. |
fixedfy |
length of follow-up in years. |
Emin |
lower limit of eGFR at baseline. |
Emax |
upper limit of eGFR at baseline. |
sigma |
within-patient standard deviation. |
Sigma |
between-patient standard deviation. |
m |
number of equidistant visits. |
theta |
coefficient of dependence of eGFR values and the risk of KFRT. |
phi |
coefficient of proportionality (between 0 and 1) of the treatment effect. The case of 0 corresponds to the uniform treatment effect. |
Value
a list containing the dataset GFR
for longitudinal measurements of eGFR and the competing KFRT events, the dataset ADET
for the time-to-event kidney outcomes (sustained declines or sustained low levels of eGFR), and the combined HCE
dataset for the kidney hierarhical composite endpoint.
See Also
simHCE()
for a general function of simulating hce
datasets.
Examples
# Example 1
set.seed(2022)
L <- simKHCE(n = 1000, CM_A = -3.25)
dat <- L$HCE
calcWO(dat)