Description Usage Arguments Details Value Note Author(s) See Also

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.

1 |

`formula` |
either a formula or a previously fitted model |

`...` |
other arguments to the specific method |

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.)

An object of class `survfit`

containing one or more survival curves.

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.

Terry Therneau

`survfit.formula`

,
`survfit.coxph`

,
`survfit.object`

, `print.survfit`

,
`plot.survfit`

, `quantile.survfit`

,
`summary.survfit`

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