Fit a Cox proportional-hazards model for one bootstrap replicate

Usage

fit_cox(data, formula, select)

Arguments

data: A data frame - one bootstrap replicate.
formula: Model formula offering the candidate terms.
select: List with method ("stepwise" or "none"), sle, sls, max_steps. %bootreg equivalents: SELECT=, SLE=, SLS=, MAXSTEP=.

Value

Named numeric vector of kept coefficients, or NULL if the fit errored. Cox models carry no intercept, so none appears in the result - which means a replicate where selection kept nothing returns a zero-length vector, not NULL, and counts as a valid replicate.

Details

Divergence: PROC PHREG SELECTION=STEPWISE enters a term on the score chi-square. R has no score test for a Cox model - anova.coxph() accepts test = "Rao" but silently ignores it and always returns the likelihood-ratio test - so entry here is by likelihood ratio. The two agree asymptotically and differ only for a term sitting on the entry threshold, so a screen will usually select the same set and may occasionally differ on a borderline candidate. Removal is Wald, matching the macro.

Examples

if (requireNamespace("survival", quietly = TRUE)) {
  set.seed(2)
  n  <- 200
  df <- data.frame(time = rexp(n), status = rbinom(n, 1, 0.7),
                   x1 = rnorm(n), noise = rnorm(n))

  fit_cox(df, survival::Surv(time, status) ~ x1 + noise,
          list(method = "stepwise", sle = 0.10, sls = 0.05, max_steps = 0))
}
#>      noise 
#> -0.1851346