Let's say I applied survival analysis on the following df
# Load necessary packages
library(survival)
# Generate example survival data (time to event and event status)
set.seed(123)
n <- 100
time <- rexp(n, rate = 0.1) # Exponential survival times (you can replace this with your own dataset)
status <- sample(0:1, n, replace = TRUE) # Censoring status (0: censored, 1: event)
# Create a survival object
surv_object <- Surv(time, status)
# Fit Kaplan-Meier survival curve
km_fit <- survfit(surv_object ~ 1)
the output of km_fit is as follows
Call: survfit(formula = surv_object ~ 1)
n events median 0.95LCL 0.95UCL
[1,] 100 52 14.6 10.7 17.3
However the data frame that includes the median and its confidence interval, I am not able to extract it.
Under the hood, the print method for objects of class survfit
calls the survmean()
function (which is not exported from the survival
package namespace). You can call it directly with survival:::survmean()
. In this case, if you step through the survival:::print.survfit()
function using debug
, you'll find that it sets the rmean
argument to "none"
. Here's how you could get the matrix you're looking for:
library(survival)
# Generate example survival data (time to event and event status)
set.seed(123)
n <- 100
time <- rexp(n, rate = 0.1) # Exponential survival times (you can replace this with your own dataset)
status <- sample(0:1, n, replace = TRUE) # Censoring status (0: censored, 1: event)
# Create a survival object
surv_object <- Surv(time, status)
# Fit Kaplan-Meier survival curve
km_fit <- survfit(surv_object ~ 1)
km_fit
#> Call: survfit(formula = surv_object ~ 1)
#>
#> n events median 0.95LCL 0.95UCL
#> [1,] 100 52 14.6 10.7 17.3
survival:::survmean(km_fit, rmean="none")$matrix
#> records n.max n.start events median 0.95LCL 0.95UCL
#> 100.00000 100.00000 100.00000 52.00000 14.63301 10.67213 17.31154
Created on 2023-09-21 with reprex v2.0.2