EVOLUTION-MANAGER
Edit File: glance.coxph.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: Glance at a(n) coxph object</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 glance.coxph {broom}"><tr><td>glance.coxph {broom}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Glance at a(n) coxph object</h2> <h3>Description</h3> <p>Glance accepts a model object and returns a <code><a href="../../tibble/html/tibble.html">tibble::tibble()</a></code> with exactly one row of model summaries. The summaries are typically goodness of fit measures, p-values for hypothesis tests on residuals, or model convergence information. </p> <p>Glance never returns information from the original call to the modeling function. This includes the name of the modeling function or any arguments passed to the modeling function. </p> <p>Glance does not calculate summary measures. Rather, it farms out these computations to appropriate methods and gathers the results together. Sometimes a goodness of fit measure will be undefined. In these cases the measure will be reported as <code>NA</code>. </p> <p>Glance returns the same number of columns regardless of whether the model matrix is rank-deficient or not. If so, entries in columns that no longer have a well-defined value are filled in with an <code>NA</code> of the appropriate type. </p> <h3>Usage</h3> <pre> ## S3 method for class 'coxph' glance(x, ...) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>A <code>coxph</code> object returned from <code><a href="../../survival/html/coxph.html">survival::coxph()</a></code>.</p> </td></tr> <tr valign="top"><td><code>...</code></td> <td> <p>Additional arguments. Not used. Needed to match generic signature only. <strong>Cautionary note:</strong> Misspelled arguments will be absorbed in <code>...</code>, where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass <code>conf.lvel = 0.9</code>, all computation will proceed using <code>conf.level = 0.95</code>. Additionally, if you pass <code>newdata = my_tibble</code> to an <code><a href="reexports.html">augment()</a></code> method that does not accept a <code>newdata</code> argument, it will use the default value for the <code>data</code> argument.</p> </td></tr> </table> <h3>Value</h3> <p>A <code><a href="../../tibble/html/tibble.html">tibble::tibble()</a></code> with exactly one row and columns: </p> <table summary="R valueblock"> <tr valign="top"><td><code>AIC</code></td> <td> <p>Akaike's Information Criterion for the model.</p> </td></tr> <tr valign="top"><td><code>BIC</code></td> <td> <p>Bayesian Information Criterion for the model.</p> </td></tr> <tr valign="top"><td><code>logLik</code></td> <td> <p>The log-likelihood of the model. [stats::logLik()] may be a useful reference.</p> </td></tr> <tr valign="top"><td><code>n</code></td> <td> <p>The total number of observations.</p> </td></tr> <tr valign="top"><td><code>nevent</code></td> <td> <p>Number of events.</p> </td></tr> <tr valign="top"><td><code>nobs</code></td> <td> <p>Number of observations used.</p> </td></tr> </table> <p>See survival::coxph.object for additional column descriptions. </p> <h3>See Also</h3> <p><code><a href="reexports.html">glance()</a></code>, <code><a href="../../survival/html/coxph.html">survival::coxph()</a></code> </p> <p>Other coxph tidiers: <code><a href="augment.coxph.html">augment.coxph</a>()</code>, <code><a href="tidy.coxph.html">tidy.coxph</a>()</code> </p> <p>Other survival tidiers: <code><a href="augment.coxph.html">augment.coxph</a>()</code>, <code><a href="augment.survreg.html">augment.survreg</a>()</code>, <code><a href="glance.aareg.html">glance.aareg</a>()</code>, <code><a href="glance.cch.html">glance.cch</a>()</code>, <code><a href="glance.pyears.html">glance.pyears</a>()</code>, <code><a href="glance.survdiff.html">glance.survdiff</a>()</code>, <code><a href="glance.survexp.html">glance.survexp</a>()</code>, <code><a href="glance.survfit.html">glance.survfit</a>()</code>, <code><a href="glance.survreg.html">glance.survreg</a>()</code>, <code><a href="tidy.aareg.html">tidy.aareg</a>()</code>, <code><a href="tidy.cch.html">tidy.cch</a>()</code>, <code><a href="tidy.coxph.html">tidy.coxph</a>()</code>, <code><a href="tidy.pyears.html">tidy.pyears</a>()</code>, <code><a href="tidy.survdiff.html">tidy.survdiff</a>()</code>, <code><a href="tidy.survexp.html">tidy.survexp</a>()</code>, <code><a href="tidy.survfit.html">tidy.survfit</a>()</code>, <code><a href="tidy.survreg.html">tidy.survreg</a>()</code> </p> <h3>Examples</h3> <pre> library(survival) cfit <- coxph(Surv(time, status) ~ age + sex, lung) tidy(cfit) tidy(cfit, exponentiate = TRUE) lp <- augment(cfit, lung) risks <- augment(cfit, lung, type.predict = "risk") expected <- augment(cfit, lung, type.predict = "expected") glance(cfit) # also works on clogit models resp <- levels(logan$occupation) n <- nrow(logan) indx <- rep(1:n, length(resp)) logan2 <- data.frame( logan[indx, ], id = indx, tocc = factor(rep(resp, each = n)) ) logan2$case <- (logan2$occupation == logan2$tocc) cl <- clogit(case ~ tocc + tocc:education + strata(id), logan2) tidy(cl) glance(cl) library(ggplot2) ggplot(lp, aes(age, .fitted, color = sex)) + geom_point() ggplot(risks, aes(age, .fitted, color = sex)) + geom_point() ggplot(expected, aes(time, .fitted, color = sex)) + geom_point() </pre> <hr /><div style="text-align: center;">[Package <em>broom</em> version 0.7.0 <a href="00Index.html">Index</a>]</div> </body></html>