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Get the survival probability at a given time

surv_prob.Rd

This function has been superseded by bkstat::predict_surv_prob. Get the survival probability at a given time. A wrapper for survival:::summary.survfit().

Usage

surv_prob(df, formula, times, ...)

Arguments

df

A data frame.

formula

A survival formula: Surv(time, time2, event) ~ variable.

times

A numeric vector of times.

...

Optional arguments passed to survival:::summary.survfit().

Value

data.frame

Examples

#----------------------------------------------------------------------------
# surv_prob() examples.
#----------------------------------------------------------------------------
library(survival)
library(bkstat)

plot(survfit(formula = Surv(futime, death) ~ trt, data = myeloid))

surv_prob(
  df = myeloid,
  formula = Surv(futime, death) ~ trt,
  times = c(100, 500, 2000)
)
#>   strata time   n n_at_risk n_events n_censored surv_prob  lower_ci  upper_ci
#> 1  trt=A  100 317       277       20         20 0.9338742 0.9062728 0.9623161
#> 2  trt=A  500 317       167      105          5 0.5764415 0.5226442 0.6357763
#> 3  trt=A 2000 317        38       46         83 0.4026241 0.3473989 0.4666283
#> 4  trt=B  100 329       302       20          7 0.9382070 0.9123374 0.9648102
#> 5  trt=B  500 329       222       75          5 0.7027906 0.6543967 0.7547632
#> 6  trt=B 2000 329        49       53        120 0.5305176 0.4778832 0.5889493
#>   ci_level ci_type
#> 1     0.95     log
#> 2     0.95     log
#> 3     0.95     log
#> 4     0.95     log
#> 5     0.95     log
#> 6     0.95     log
surv_prob(
  df = myeloid,
  formula = Surv(futime, death) ~ 1,
  times = c(100, 500, 2000)
)
#>    strata time   n n_at_risk n_events n_censored surv_prob  lower_ci  upper_ci
#> 1 Overall  100 646       579       40         27 0.9361388 0.9171812 0.9554883
#> 2 Overall  500 646       389      180         10 0.6422112 0.6053763 0.6812874
#> 3 Overall 2000 646        87       99        203 0.4691332 0.4299483 0.5118894
#>   ci_level ci_type
#> 1     0.95     log
#> 2     0.95     log
#> 3     0.95     log
surv_prob(
  df = myeloid,
  formula = Surv(futime, death) ~ trt + sex,
  times = c(100, 500, 2000)
)
#>          strata time   n n_at_risk n_events n_censored surv_prob  lower_ci
#> 1  trt=A, sex=f  100 189       164        9         16 0.9495725 0.9179883
#> 2  trt=A, sex=f  500 189       105       56          3 0.6225603 0.5540913
#> 3  trt=A, sex=f 2000 189        29       24         52 0.4673843 0.3950737
#> 4  trt=A, sex=m  100 128       113       11          4 0.9117194 0.8632355
#> 5  trt=A, sex=m  500 128        62       49          2 0.5119349 0.4306712
#> 6  trt=A, sex=m 2000 128         9       22         31 0.3109665 0.2343301
#> 7  trt=B, sex=f  100 172       159       10          3 0.9411765 0.9064629
#> 8  trt=B, sex=f  500 172       108       47          4 0.6580567 0.5897754
#> 9  trt=B, sex=f 2000 172        28       24         56 0.5064618 0.4349031
#> 10 trt=B, sex=m  100 157       143       10          4 0.9349196 0.8967147
#> 11 trt=B, sex=m  500 157       114       28          1 0.7511892 0.6856341
#> 12 trt=B, sex=m 2000 157        21       29         64 0.5568278 0.4828245
#>     upper_ci ci_level ci_type
#> 1  0.9822433     0.95     log
#> 2  0.6994900     0.95     log
#> 3  0.5529299     0.95     log
#> 4  0.9629263     0.95     log
#> 5  0.6085323     0.95     log
#> 6  0.4126666     0.95     log
#> 7  0.9772195     0.95     log
#> 8  0.7342433     0.95     log
#> 9  0.5897946     0.95     log
#> 10 0.9747523     0.95     log
#> 11 0.8230121     0.95     log
#> 12 0.6421737     0.95     log