kmest function

Kaplan-Meier Estimates of Survival Curve

Obtains the Kaplan-Meier estimates of the survival curve.

kmest(
  data,
  rep = "",
  stratum = "",
  time = "time",
  event = "event",
  conftype = "log-log",
  conflev = 0.95,
  keep_censor = 0L
)

Arguments

• data: The input data frame that contains the following variables:

  • rep: The replication for by-group processing.
  • stratum: The stratum.
  • time: The possibly right-censored survival time.
  • event: The event indicator.

• rep: The name(s) of the replication variable(s) in the input data.

• stratum: The name(s) of the stratum variable(s) in the input data.

• time: The name of the time variable in the input data.

• event: The name of the event variable in the input data.

• conftype: The type of the confidence interval. One of "none", "plain", "log", "log-log" (the default), or "arcsin". The arcsin option bases the intervals on asin(sqrt(survival)).

• conflev: The level of the two-sided confidence interval for the survival probabilities. Defaults to 0.95.

• keep_censor: Whether to retain the censoring time in the output data frame.

Returns

A data frame with the following variables:

• size: The number of subjects in the stratum.
• time: The event time.
• nrisk: The number of subjects at risk.
• nevent: The number of subjects having the event.
• ncensor: The number of censored subjects.
• survival: The Kaplan-Meier estimate of the survival probability.
• stderr: The standard error of the estimated survival probability based on the Greendwood formula.
• lower: The lower bound of confidence interval if requested.
• upper: The upper bound of confidence interval if requested.
• conflev: The level of confidence interval if requested.
• conftype: The type of confidence interval if requested.
• stratum: The stratum.
• rep: The replication.

Examples

kmest(data = aml, stratum = "x", time = "time", event = "status")

Author(s)

Kaifeng Lu, kaifenglu@gmail.com