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: Tidy a(n) clm 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 tidy.clm {broom}"><tr><td>tidy.clm {broom}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Tidy a(n) clm object</h2> <h3>Description</h3> <p>Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return. </p> <h3>Usage</h3> <pre> ## S3 method for class 'clm' tidy( x, conf.int = FALSE, conf.level = 0.95, conf.type = c("profile", "Wald"), exponentiate = FALSE, ... ) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>A <code>clm</code> object returned from <code><a href="../../ordinal/html/clm.html">ordinal::clm()</a></code>.</p> </td></tr> <tr valign="top"><td><code>conf.int</code></td> <td> <p>Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to <code>FALSE</code>.</p> </td></tr> <tr valign="top"><td><code>conf.level</code></td> <td> <p>The confidence level to use for the confidence interval if <code>conf.int = TRUE</code>. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.</p> </td></tr> <tr valign="top"><td><code>conf.type</code></td> <td> <p>Whether to use <code>"profile"</code> or <code>"Wald"</code> confidence intervals, passed to the <code>type</code> argument of <code><a href="../../ordinal/html/confint.clm.html">ordinal::confint.clm()</a></code>. Defaults to <code>"profile"</code>.</p> </td></tr> <tr valign="top"><td><code>exponentiate</code></td> <td> <p>Logical indicating whether or not to exponentiate the the coefficient estimates. This is typical for logistic and multinomial regressions, but a bad idea if there is no log or logit link. Defaults to <code>FALSE</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>Details</h3> <p>In <code style="white-space: pre;">broom 0.7.0</code> the <code>coefficient_type</code> column was renamed to <code>coef.type</code>, and the contents were changed as well. </p> <p>Note that <code>intercept</code> type coefficients correspond to <code>alpha</code> parameters, <code>location</code> type coefficients correspond to <code>beta</code> parameters, and <code>scale</code> type coefficients correspond to <code>zeta</code> parameters. </p> <h3>Value</h3> <p>A <code><a href="../../tibble/html/tibble.html">tibble::tibble()</a></code> with columns: </p> <table summary="R valueblock"> <tr valign="top"><td><code>conf.high</code></td> <td> <p>Upper bound on the confidence interval for the estimate.</p> </td></tr> <tr valign="top"><td><code>conf.low</code></td> <td> <p>Lower bound on the confidence interval for the estimate.</p> </td></tr> <tr valign="top"><td><code>estimate</code></td> <td> <p>The estimated value of the regression term.</p> </td></tr> <tr valign="top"><td><code>p.value</code></td> <td> <p>The two-sided p-value associated with the observed statistic.</p> </td></tr> <tr valign="top"><td><code>statistic</code></td> <td> <p>The value of a T-statistic to use in a hypothesis that the regression term is non-zero.</p> </td></tr> <tr valign="top"><td><code>std.error</code></td> <td> <p>The standard error of the regression term.</p> </td></tr> <tr valign="top"><td><code>term</code></td> <td> <p>The name of the regression term.</p> </td></tr> </table> <h3>See Also</h3> <p><a href="reexports.html">tidy</a>, <code><a href="../../ordinal/html/clm.html">ordinal::clm()</a></code>, <code><a href="../../ordinal/html/confint.clm.html">ordinal::confint.clm()</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.clmm.html">glance.clmm</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.polr.html">tidy.polr</a>()</code>, <code><a href="tidy.svyolr.html">tidy.svyolr</a>()</code> </p> <h3>Examples</h3> <pre> library(ordinal) fit <- clm(rating ~ temp * contact, data = wine) tidy(fit) tidy(fit, conf.int = TRUE, conf.level = 0.9) tidy(fit, conf.int = TRUE, conf.type = "Wald", exponentiate = TRUE) glance(fit) augment(fit, type.predict = "prob") augment(fit, type.predict = "class") fit2 <- clm(rating ~ temp, 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>