EVOLUTION-MANAGER
Edit File: cluster.html
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Identify clusters.</title> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <link rel="stylesheet" type="text/css" href="R.css" /> </head><body> <table width="100%" summary="page for cluster {survival}"><tr><td>cluster {survival}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2> Identify clusters. </h2> <h3>Description</h3> <p>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 <code>cluster()</code> in a formula implies that robust sandwich variance estimators are desired.</p> <h3>Usage</h3> <pre> cluster(x) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>A character, factor, or numeric variable. </p> </td></tr> </table> <h3>Details</h3> <p>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. </p> <h3>Value</h3> <p><code>x</code> </p> <h3>See Also</h3> <p><code><a href="coxph.html">coxph</a></code>, <code><a href="survreg.html">survreg</a></code> </p> <h3>Examples</h3> <pre> 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')) </pre> <hr /><div style="text-align: center;">[Package <em>survival</em> version 2.44-1.1 <a href="00Index.html">Index</a>]</div> </body></html>