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This function calculates the one minus Kaplan-Meier estimator of adverse events (while censoring all competing events) observed in [0, tau]. Please also refer to formula (4) in Stegherr et al. (2021) .

Usage

one_minus_kaplan_meier(data, tau)

Arguments

data

(data.frame)
with columns including

  • time_to_event: Time to the first AE, death or soft competing event.

  • type_of_event: 0 for censored, 1 for AE, 2 for death, 3 for soft competing event.

tau

(number)
milestone at which One Minus Kaplan-Meier is computed.

Value

(vector)
with the following entries:

  • ae_prob: Estimated probability of AE.

  • ae_prob_var: Variance of that estimate.

References

Stegherr R, Beyersmann J, Jehl V, Rufibach K, Leverkus F, Schmoor C, Friede T (2021). “Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Rationale and statistical concept of a meta-analytic study.” Biometrical Journal, 63(3), 650-670. doi:10.1002/bimj.201900347 , https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.201900347, https://onlinelibrary.wiley.com/doi/abs/10.1002/bimj.201900347.

Examples

set.seed(123)
dat <- generate_data(n = 5, cens = c(2, 5), haz_ae = 2, haz_death = 3, haz_soft = 5)
one_minus_kaplan_meier(dat, tau = 4)
#>     ae_prob ae_prob_var 
#>       0.600       0.088