| KaplanMeier | R Documentation | 
Computes the Kaplan-Meier estimator for the survival function of right censored data.
KaplanMeier(x, data, censored, conf.type="plain", conf.int = 0.95)
| x | Vector with points to evaluate the estimator in. | 
| data | Vector of  | 
| censored | Vector of  | 
| conf.type | Type of confidence interval, see  | 
| conf.int | Confidence level of the two-sided confidence interval, see  | 
We consider the random right censoring model where one observes Z = \min(X,C)
where X is the variable of interest and C is the censoring variable.
This function is merely a wrapper for survfit.formula from survival.
This estimator is only suitable for right censored data. When the data are interval censored, one can use the Turnbull estimator implemented in Turnbull.
A list with following components:
| surv | A vector of length  | 
| fit | The output from the call to  | 
Tom Reynkens
Kaplan, E. L. and Meier, P. (1958). "Nonparametric Estimation from Incomplete Observations." Journal of the American Statistical Association, 53, 457–481.
survfit.formula, Turnbull
data <- c(1, 2.5, 3, 4, 5.5, 6, 7.5, 8.25, 9, 10.5)
censored <- c(0, 1, 0, 0, 1, 0, 1, 1, 0, 1)
x <- seq(0, 12, 0.1)
# Kaplan-Meier estimator
plot(x, KaplanMeier(x, data, censored)$surv, type="s", ylab="Kaplan-Meier estimator")
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