hce (version 0.8.0)

simKHCE: 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
)

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.

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.

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)