Tests the null hypothesis that the proportion of observations susceptible to the event = 1 against the alternative that the proportion of observations susceptible to the event is < 1. If the null hypothesis is rejected, there is a significant cured fraction.
Arguments
- object
a
survfitobject.- reps
number of simulations on which to base the p-value (default = 1000).
- seed
optional random seed.
- plot
logical. If TRUE a histogram of the estimated susceptible proportions over all simulations is produced.
- b
optional. If specified the maximum observed time for the uniform distribution for generating the censoring times. If not specified, an exponential model is used for generating the censoring times (default).
Value
- proportion_susceptible
estimated proportion of susceptibles
- proportion_cured
estimated proportion of those cured
- p_value
p-value testing the null hypothesis that the proportion of susceptibles = 1 (cured fraction = 0) against the alternative that the proportion of susceptibles < 1 (non-zero cured fraction)
- time_95_percent_of_events
estimated time at which 95% of events should have occurred
References
Maller, R. A. and Zhou, X. (1996) Survival Analysis with Long-Term Survivors. John Wiley & Sons.
Examples
library(survival)
withr::local_seed(1234)
temp <- generate_cure_data(n = 100, j = 10, n_true = 10, a = 1.8)
training <- temp$training
km_fit <- survfit(Surv(Time, Censor) ~ 1, data = training)
nonzerocure_test(km_fit)
#> $proportion_susceptible
#> [1] 0.5129002
#>
#> $proportion_cured
#> [1] 0.4870998
#>
#> $p_value
#> [1] 0.135
#>
#> $time_95_percent_of_events
#> [1] 3.910758
#>