trtswitch (version 0.2.2)

kmest: Kaplan-Meier Estimates of Survival Curve

Description

Obtains the Kaplan-Meier estimates of the survival curve.

Usage

kmest(
  data,
  rep = "",
  stratum = "",
  time = "time",
  time2 = "",
  event = "event",
  weight = "",
  conftype = "log-log",
  conflev = 0.95,
  keep_censor = FALSE
)

Value

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.

• surv: The Kaplan-Meier estimate of the survival probability.

• sesurv: 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.

Arguments

data

The input data frame that contains the following variables:

• rep: The replication for by-group processing.

• stratum: The stratum.

• time: The follow-up time for right censored data, or the left end of each interval for counting process data.

• time2: The right end of each interval for counting process data. Intervals are assumed to be open on the left and closed on the right, and event indicates whether an event occurred at the right end of each interval.

• event: The event indicator, 1=event, 0=no event.

• weight: The weight for each observation.

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 or the left end of each interval for counting process data in the input data.

time2

The name of the right end of each interval for counting process data in the input data.

event

The name of the event variable in the input data.

weight

The name of the weight 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.

Author

Kaifeng Lu,

Examples

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