EVOLUTION-MANAGER
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<!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: Compute Expected Survival</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 survexp.fit {survival}"><tr><td>survexp.fit {survival}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2> Compute Expected Survival </h2> <h3>Description</h3> <p>Compute expected survival times. </p> <h3>Usage</h3> <pre> survexp.fit(group, x, y, times, death, ratetable) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>group</code></td> <td> <p>if there are multiple survival curves this identifies the group, otherwise it is a constant. Must be an integer.</p> </td></tr> <tr valign="top"><td><code>x</code></td> <td> <p>A matrix whose columns match the dimensions of the <code>ratetable</code>, in the correct order. </p> </td></tr> <tr valign="top"><td><code>y</code></td> <td> <p>the follow up time for each subject. </p> </td></tr> <tr valign="top"><td><code>times</code></td> <td> <p>the vector of times at which a result will be computed. </p> </td></tr> <tr valign="top"><td><code>death</code></td> <td> <p>a logical value, if <code>TRUE</code> the conditional survival is computed, if <code>FALSE</code> the cohort survival is computed. See <code><a href="survexp.html">survexp</a></code> for more details. </p> </td></tr> <tr valign="top"><td><code>ratetable</code></td> <td> <p>a rate table, such as <code>survexp.uswhite</code>. </p> </td></tr> </table> <h3>Details</h3> <p>For conditional survival <code>y</code> 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. </p> <p>For an exact estimate <code>times</code> should be a superset of <code>y</code>, 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 <code>times</code> 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. </p> <p>For a subgroup of size 1 and <code>times</code> > <code>y</code>, 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. </p> <h3>Value</h3> <p>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. </p> <h3>Warning</h3> <p>Most users will call the higher level routine <code>survexp</code>. Consequently, this function has very few error checks on its input arguments. </p> <h3>See Also</h3> <p><code><a href="survexp.html">survexp</a></code>, <code><a href="survexp.us.html">survexp.us</a></code>. </p> <hr /><div style="text-align: center;">[Package <em>survival</em> version 2.44-1.1 <a href="00Index.html">Index</a>]</div> </body></html>