# residuals.survfit: IJ residuals from a survfit object. In survival: Survival Analysis

## Description

Return infinitesimal jackknife residuals from a survfit object, for the survival, cumulative hazard, or restricted mean time in state (RMTS).

## Usage

 ```1 2 3 4``` ```## S3 method for class 'survfit' residuals(object, times, type="pstate", collapse, weighted=FALSE, method=1, ...) ```

## Arguments

 `object` a `survfit` object `times` a vector of times at which the residuals are desired `type` the type of residual, see below `collapse` add the residuals for all subjects in a cluster `weighted` weight the residuals by each observation's weight `method` controls a choice of algorithm. Current an internal debugging option. `...` arguments for other methods

## Details

This function is designed to efficiently compute the leverage residuals at a small number of time points; a primary use is the creation of pseudo-values. If the residuals at all time points are needed, e.g. to compute a robust pointwise confidence interval for the survival curve, then this can be done more efficiently using the `influence` argument of the underlying `survfit` function. But be aware that such matrices can get very large.

The residuals are the impact of each observation or cluster on the resulting probability in state curves at the given time points, the cumulative hazard curv`surv` at those time points, or the expected sojourn time in each state up to the given time points. For a simple Kaplan-Meier the `survfit` object contains only the probability in the "initial" state, i.e., the survival fraction. For the KM case the sojourn time, the expected amount of time spent in the initial state, up to the specified endpoint, is more commonly known as the restricted mean survival time (RMST). For a multistate model this same quantity is also referred to as the restricted mean time in state (RMTS). It can be computed as the area under the respective probability in state curve. The program allows any of `pstate`, `surv`, `cumhaz`, `chaz`, `sojourn`, `rmst`, `rmts` or `auc` for the type argument, ignoring upper/lowercase, so users can choose whichever abbreviation they like best.

When `collapse=TRUE` the result has the cluster identifier (which defaults to the `id` variable) as the dimname for the first dimension. If the `fit` object contains more than one curve, and the same identifier is reused in two different curves this approach does not work and the routine will stop with an error. In principle this is not necessary, e.g., the result could contain two rows with the same label, showing the separate effect on each curve, but this was deemed too confusing.

## Value

A matrix or array with one row per observation or cluster, and one column for each value in `times`. For a multi-state model the three dimensions are observation, time and state. For cumulative hazard, the last dimension is the set of transitions. (A competing risks model for instance has 3 states and 2 transitions.)

`survfit`, `survfit.formula`

## Examples

 ```1 2``` ```fit <- survfit(Surv(time, status) ~ x, aml) resid(fit, times=c(24, 48), type="RMTS") ```

### Example output

```NULL
```

survival documentation built on Aug. 24, 2021, 5:06 p.m.