residuals.coxph {survival} | R Documentation |

## Calculate Residuals for a ‘coxph’ Fit

### Description

Calculates martingale, deviance, score or Schoenfeld residuals for a Cox proportional hazards model.

### Usage

```
## S3 method for class 'coxph'
residuals(object,
type=c("martingale", "deviance", "score", "schoenfeld",
"dfbeta", "dfbetas", "scaledsch","partial"),
collapse=FALSE, weighted= (type %in% c("dfbeta", "dfbetas")), ...)
## S3 method for class 'coxphms'
residuals(object,
type=c("martingale", "score", "schoenfeld",
"dfbeta", "dfbetas", "scaledsch"),
collapse=FALSE, weighted= FALSE, ...)
## S3 method for class 'coxph.null'
residuals(object,
type=c("martingale", "deviance","score","schoenfeld"),
collapse=FALSE, weighted= FALSE, ...)
```

### Arguments

`object` |
an object inheriting from class |

`type` |
character string indicating the type of residual desired.
Possible values are |

`collapse` |
vector indicating which rows to collapse (sum) over.
In time-dependent models more than one row data can pertain
to a single individual.
If there were 4 individuals represented by 3, 1, 2 and 4 rows of data
respectively, then |

`weighted` |
if |

`...` |
other unused arguments |

### Value

For martingale and deviance residuals, the returned object is a vector
with one element for each subject (without `collapse`

).
For score residuals it is a matrix
with one row per subject and one column per variable.
The row order will match the input data for the original fit.
For Schoenfeld residuals, the returned object is a matrix with one row
for each event and one column per variable. The rows are ordered by time
within strata, and an attribute `strata`

is attached that contains the
number of observations in each strata.
The scaled Schoenfeld residuals are used in the `cox.zph`

function.

The score residuals are each individual's contribution to the score vector.
Two transformations of
this are often more useful: `dfbeta`

is the approximate change in the
coefficient vector if that observation were dropped,
and `dfbetas`

is the approximate change in the coefficients, scaled by
the standard error for the coefficients.

### NOTE

For deviance residuals, the status variable may need to be reconstructed. For score and Schoenfeld residuals, the X matrix will need to be reconstructed.

### References

T. Therneau, P. Grambsch, and T. Fleming. "Martingale based residuals
for survival models", *Biometrika*, March 1990.

### See Also

### Examples

```
fit <- coxph(Surv(start, stop, event) ~ (age + surgery)* transplant,
data=heart)
mresid <- resid(fit, collapse=heart$id)
```

*survival*version 3.6-4 Index]