# survfit

0th

Percentile

##### Create survival curves

This function creates survival curves from either a formula (e.g. the Kaplan-Meier), a previously fitted Cox model, or a previously fitted accelerated failure time model.

Keywords
survival
##### Usage
survfit(formula, ...)
##### Arguments
formula

either a formula or a previously fitted model

other arguments to the specific method

##### Details

A survival curve is based on a tabulation of the number at risk and number of events at each unique death time. When time is a floating point number the definition of "unique" is subject to interpretation. The code uses factor() to define the set. For further details see the documentation for the appropriate method, i.e., ?survfit.formula or ?survfit.coxph.

A survfit object may contain a single curve, a set of curves, or a matrix curves. Predicted curves from a coxph model have one row for each stratum in the Cox model fit and one column for each specified covariate set. Curves from a multi-state model have one row for each stratum and a column for each state, the strata correspond to predictors on the right hand side of the equation. The default printing and plotting order for curves is by column, as with other matrices.

Curves can be subscripted using either a single or double subscript. If the set of curves is a matrix, as in the above, and one of the dimensions is 1 then the code allows a single subscript to be used. (That is, it is not quite as general as using a single subscript for a numeric matrix.)

##### Value

An object of class survfit containing one or more survival curves.

##### Note

Older releases of the code also allowed the specification for a single curve to omit the right hand of the formula, i.e., survfit(Surv(time, status)), in which case the formula argument is not actually a formula. Handling this case required some non-standard and fairly fragile manipulations, and this case is no longer supported.

survfit.formula, survfit.coxph, survfit.object, print.survfit, plot.survfit, quantile.survfit, summary.survfit