# cluster

From survival v2.44-1.1
by Terry Therneau

##### Identify clusters.

This is a special function used in the context of survival models. It
identifies correlated groups of observations, and is used on the right hand
side of a formula.
Using `cluster()`

in a formula implies that
robust sandwich variance estimators are desired.

- Keywords
- survival

##### Usage

`cluster(x)`

##### Arguments

- x
A character, factor, or numeric variable.

##### Details

The function's only action is semantic, to mark a variable as the cluster indicator. The resulting variance is what is known as the ``working independence'' variance in a GEE model. Note that one cannot use both a frailty term and a cluster term in the same model, the first is a mixed-effects approach to correlation and the second a GEE approach, and these don't mix.

##### Value

`x`

##### See Also

##### Examples

```
# NOT RUN {
marginal.model <- coxph(Surv(time, status) ~ rx + cluster(litter), rats,
subset=(sex=='f'))
frailty.model <- coxph(Surv(time, status) ~ rx + frailty(litter), rats,
subset=(sex=='f'))
# }
```

*Documentation reproduced from package survival, version 2.44-1.1, License: LGPL (>= 2)*

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