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BP-based model survival curves

Source: R/survfit.R
survfit.spbp.Rd

Compute survival curves for a fitted spbp model.

Usage

# S3 method for class 'spbp'
survfit(
  formula,
  newdata,
  times,
  se.fit = TRUE,
  interval = 0.95,
  type = c("log", "log-log", "plain"),
  ...
)

Arguments

formula

An object of class "spbp" returned by spbp.

newdata

Optional data frame used to obtain survival curves for specific covariate values.

times

Optional numeric vector of time points at which to return estimates.

se.fit

Logical; if TRUE, compute standard errors.

interval

Confidence level for intervals (e.g. 0.95).

type

Character; confidence interval transformation. One of "log", "log-log", or "plain".

...

Further arguments (currently ignored or reserved for future use).

Value

An object of class "survfit".

See also

spbp, survfit.

Examples

library(spsurv)
data(veteran, package = "survival")
#> Warning: data set ‘veteran’ not found
fit <- bpph(Surv(time, status) ~ karno + factor(celltype), data = veteran)
#> Priors are ignored because the MLE approach is used.
survfit(fit)
#> Call: survfit.spbp(formula = fit)
#> 
#>        n events median 0.95LCL 0.95UCL
#> [1,] 137    128     73       1      NA