popEpi (version 0.3.1)

summary.survtab: Summarize a survtab Object

Description

Summary method function for survtab objects; see survtab_ag. Returns estimates at given time points or all time points.

Usage

"summary"(object, t = NULL, subset = NULL, q = NULL, ...)

Arguments

object

a survtab object

t

a vector of times at which time points to print summary table of survival function estimates by strata; will automatically use values in breaks used to split data for aggregation closest to these values, so e.g. supplyig t = c(2.5, 5.1) with data that was split by the breaks seq(0, 5, 1/12) causes the times c(2.5, 5.0) to be used. Since the estimates at the time points closest to t are selected, values of t are compared with column Tstop in the data. If NULL, prints all rows.

subset

a logical condition to subset results table by before printing; use this to limit to a certain stratum. E.g. subset = sex == "male"

q

a named list of quantiles to include in returned data set. E.g. list(surv.obs = 0.5) for rows closest to the median survival for each strata in the survtab object. See Examples.

...

unused; required for congruence with other summary methods

Examples

library(Epi)
library(survival)

## NOTE: recommended to use factor status variable
x <- Lexis(entry = list(FUT = 0, AGE = dg_age, CAL = get.yrs(dg_date)), 
           exit = list(CAL = get.yrs(ex_date)), 
           data = sire[sire$dg_date < sire$ex_date, ],
           exit.status = factor(status, levels = 0:2, 
           labels = c("alive", "canD", "othD")), 
           merge = TRUE)
## pretend some are male
set.seed(1L)
x$sex <- rbinom(nrow(x), 1, 0.5)
## observed survival
st <- survtab(Surv(time = FUT, event = lex.Xst) ~ sex, data = x, 
                  surv.type = "cif.obs",
                  breaks = list(FUT = seq(0, 5, 1/12)))

## estimates at full years of follow-up
summary(st, t = 1:5)

## interval estimate closest to 75th percentile 
## (just switch 0.75 to 0.5 for median survival, etc.)
summary(st, q = list(surv.obs = 0.75))
## multiple quantiles
summary(st, q = list(surv.obs = c(0.75, 0.90), CIF_canD = 0.20))

## if you want all estimates in a new data.frame, you can also simply do

x <- as.data.frame(st)