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A fixed-support model-based bootstrap keeps the support selected in the observed data fixed throughout bootstrap analysis. Procedure-level re-selection instead repeats Cox-Lasso selection and subsequent refitting in each bootstrap sample and therefore describes the repeated data-adaptive procedure.
In coxlasso_boot(inference = "conditional"), the term conditional means that the observed selected support is retained as the working model; it does not denote formal conditioning on the complete selection event. Re-selection is therefore exposed separately through coxlasso_boot_reselect().
The interface supports fixed_support, reselect_fixed_lambda, reselect_cv_min, reselect_cv_1se, and reselect_aic. The first three form the main comparison; CV-1SE and AIC are tuning sensitivities.
For a coordinate that is not selected in a bootstrap sample, the coefficient is recorded as zero on the original p-dimensional scale. A failed non-empty Cox refit is different: it is recorded as missing and contributes to the refit-success diagnostic rather than being treated as non-selection.
set.seed(2026)
n <- 100
p <- 6
X <- matrix(rnorm(n * p), n, p)
colnames(X) <- paste0("x", seq_len(p))
beta <- c(0.8, -0.6, 0.4, 0, 0, 0)
T <- rexp(n, rate = 0.06 * exp(drop(X %*% beta)))
C <- rexp(n, rate = 0.04)
time <- pmin(T, C)
status <- as.integer(T <= C)
library(selSurv)
fit <- coxlasso_boot_reselect(
X, time, status,
B = 50,
methods = c("fixed_support", "reselect_fixed_lambda", "reselect_cv_min"),
seed = 2026,
nfolds = 5,
standardize = TRUE
)
fit_summary <- summary(fit)
fit_summary$diagnostics
fit_summary$intervalsFor publication-scale analyses, use a larger B; small values are appropriate only for demonstrating the interface.
rng_mode = "independent_streams" is the normal default and makes results for a named method invariant to the order in which methods are requested. rng_mode = "legacy_nki70" is retained only to reproduce the archived NKI70 production analysis and is not recommended for new analyses.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.