Last data update: 2014.03.03

R: Estimates survival using Kaplan-Meier estimation
 surv.km R Documentation

## Estimates survival using Kaplan-Meier estimation

### Description

Estimates the probability of survival past some specified time using Kaplan-Meier estimation

### Usage

```surv.km(tl, dl, tt, var = FALSE, conf.int = FALSE, weight.perturb = NULL,
perturb.vector = FALSE)
```

### Arguments

 `tl` observed event time of primary outcome, equal to min(T, C) where T is the event time and C is the censoring time. `dl` event indicator, equal to I(T

### Details

See documentation for delta.km for details.

### Value

A list is returned:

 `S.estimate` the estimate of survival at the time of interest, hat{S}(t) = P(T>t) `S.var ` the variance estimate of hat{S}(t); if var = TRUE or conf.int = TRUE `conf.int.normal.S` a vector of size 2; the 95% confidence interval for hat{S}(t) based on a normal approximation; if conf.int = TRUE `conf.int.quantile.S` a vector of size 2; the 95% confidence interval for hat{S}(t) based on sample quantiles of the perturbed values, described above; if conf.int = TRUE `perturb.vector` a vector of size x where x is the number of columns of the provided weight.perturb matrix (or x=500 if weight.perturb is not provided); the perturbed values of hat{S}(t); if perturb.vector = TRUE and either var=TRUE or conf.int = TRUE

Layla Parast

### References

Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481.

### Examples

```data(example_rct)
example_rct.treat = example_rct[example_rct\$treat == 1,]
surv.km(tl=example_rct.treat\$TL, dl = example_rct.treat\$DL, tt=2)
```

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