survexp.fit {survival} | R Documentation

## Compute Expected Survival

### Description

Compute expected survival times.

### Usage

    survexp.fit(group, x, y, times, death, ratetable)

### Arguments

`group` | if there are multiple survival curves this identifies the group, otherwise it is a constant. Must be an integer.
`x` | A matrix whose columns match the dimensions of the `ratetable`, in the correct order.
`y` | the follow up time for each subject.
`times` | the vector of times at which a result will be computed.
`death` | a logical value, if `TRUE` the conditional survival is computed, if `FALSE` the cohort survival is computed. See `survexp` for more details.
`ratetable` | a rate table, such as `survexp.uswhite`.

### Details

For conditional survival `y` must be the time of last follow-up or death for each subject. For cohort survival it must be the potential censoring time for each subject, ignoring death.

For an exact estimate `times` should be a superset of `y`, so that each subject at risk is at risk for the entire sub-interval of time. For a large data set, however, this can use an inordinate amount of storage and/or compute time. If the `times` spacing is more coarse than this, an actuarial approximation is used which should, however, be extremely accurate as long as all of the returned values are > .99.

For a subgroup of size 1 and `times` > `y`, the conditional method reduces to exp(-h) where h is the expected cumulative hazard for the subject over his/her observation time. This is used to compute individual expected survival.

### Value

A list containing the number of subjects and the expected survival(s) at each time point. If there are multiple groups, these will be matrices with one column per group.

### Warning

Most users will call the higher level routine `survexp`. Consequently, this function has very few error checks on its input arguments.

### See Also

`survexp`, `survexp.us`.

[Package survival version 2.41-3 Index]