Bootstrap data by sampling the same number of subjects from the original dataset by sampling with replacement.
bootdata(dat)model data to be bootstrapped
Bootstrapped data
# \donttest{
specs <- list(fixed = lKA + lCL + lV ~ 1,
random = pdDiag(lKA + lCL ~ 1),
start = c(lKA = 0.5, lCL = -3.2, lV = -1))
set.seed(99)
nboot <- 5
cat("generating", nboot, "bootstrap samples...\n")
#> generating 5 bootstrap samples...
cmat <- matrix(NA, nboot, 3)
for (i in 1:nboot)
{
# print(i)
bd <- bootdata(theo_md)
fit <- nlme_lin_cmpt(bd, par_model = specs, ncmt = 1)
cmat[i, ] <- fit$coefficients$fixed
}
dimnames(cmat)[[2]] <- names(fit$coefficients$fixed)
print(head(cmat))
#> lKA lCL lV
#> [1,] 0.05306155 1.075381 3.386794
#> [2,] 0.11497191 1.128515 3.420884
#> [3,] -0.12557953 1.058856 3.339239
#> [4,] 0.26477967 1.082458 3.410182
#> [5,] 0.42716230 1.191098 3.533160
# }