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: Glance at a(n) clmm 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.clmm {broom}"><tr><td>glance.clmm {broom}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Glance at a(n) clmm 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 'clmm' glance(x, ...) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>A <code>clmm</code> object returned from <code><a href="../../ordinal/html/clmm.html">ordinal::clmm()</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>edf</code></td> <td> <p>The effective degrees of freedom.</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>nobs</code></td> <td> <p>Number of observations used.</p> </td></tr> </table> <h3>See Also</h3> <p><a href="reexports.html">tidy</a>, <code><a href="../../ordinal/html/clmm.html">ordinal::clmm()</a></code> </p> <p>Other ordinal tidiers: <code><a href="augment.clm.html">augment.clm</a>()</code>, <code><a href="augment.polr.html">augment.polr</a>()</code>, <code><a href="glance.clm.html">glance.clm</a>()</code>, <code><a href="glance.polr.html">glance.polr</a>()</code>, <code><a href="glance.svyolr.html">glance.svyolr</a>()</code>, <code><a href="tidy.clmm.html">tidy.clmm</a>()</code>, <code><a href="tidy.clm.html">tidy.clm</a>()</code>, <code><a href="tidy.polr.html">tidy.polr</a>()</code>, <code><a href="tidy.svyolr.html">tidy.svyolr</a>()</code> </p> <h3>Examples</h3> <pre> library(ordinal) fit <- clmm(rating ~ temp + contact + (1 | judge), data = wine) tidy(fit) tidy(fit, conf.int = TRUE, conf.level = 0.9) tidy(fit, conf.int = TRUE, exponentiate = TRUE) glance(fit) fit2 <- clmm(rating ~ temp + (1 | judge), nominal = ~contact, data = wine) tidy(fit2) glance(fit2) </pre> <hr /><div style="text-align: center;">[Package <em>broom</em> version 0.7.0 <a href="00Index.html">Index</a>]</div> </body></html>