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  <main id="main" class="col-md-9"><div class="page-header">
      <img src="../logo.png" class="logo" alt=""><h1>Anova Tables for Various Statistical Models (car::Anova)</h1>
      <small class="dont-index">Source: <a href="https://github.com/rempsyc/rempsyc/blob/HEAD/R/car_Anova.R" class="external-link"><code>R/car_Anova.R</code></a></small>
      <div class="d-none name"><code>car_Anova.Rd</code></div>
    </div>

    <div class="ref-description section level2">
    <p>Compute ANOVA from the <code>car</code> package
and <code>Anova</code> function.</p>
    </div>

    <div class="section level2">
    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">car_Anova</span><span class="op">(</span></span>
<span>  <span class="va">mod</span>,</span>
<span>  <span class="va">error</span>,</span>
<span>  type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"II"</span>, <span class="st">"III"</span>, <span class="fl">2</span>, <span class="fl">3</span><span class="op">)</span>,</span>
<span>  white.adjust <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="cn">FALSE</span>, <span class="cn">TRUE</span>, <span class="st">"hc3"</span>, <span class="st">"hc0"</span>, <span class="st">"hc1"</span>, <span class="st">"hc2"</span>, <span class="st">"hc4"</span><span class="op">)</span>,</span>
<span>  vcov. <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  <span class="va">singular.ok</span>,</span>
<span>  <span class="va">...</span></span>
<span><span class="op">)</span></span></code></pre></div>
    </div>

    <div class="section level2">
    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
    <dl><dt>mod</dt>
<dd><p>lm, aov, glm, multinom, polr mlm, coxph, coxme, lme, mer, merMod, svyglm, svycoxph, rlm, or other suitable model object.</p></dd>


<dt>error</dt>
<dd><p>for a linear model, an lm model object from which the error sum of squares and degrees of freedom are to be calculated. For F-tests for a generalized linear model, a glm object from which the dispersion is to be estimated. If not specified, mod is used.</p></dd>


<dt>type</dt>
<dd><p>type of test, "II", "III", 2, or 3. Roman numerals are equivalent to the corresponding Arabic numerals.</p></dd>


<dt>white.adjust</dt>
<dd><p>if not FALSE, the default, tests use a heteroscedasticity-corrected coefficient covariance matrix; the various values of the argument specify different corrections. See the documentation for hccm for details. If white.adjust=TRUE then the "hc3" correction is selected.</p></dd>

</dl></div>
    <div class="section level2">
    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
    

<p>An object of class "anova", or "Anova.mlm", which usually is printed. For objects of class "Anova.mlm", there is also a summary method, which provides much more detail than the print method about the MANOVA, including traditional mixed-model univariate F-tests with Greenhouse-Geisser and Huynh-Feldt corrections.</p>
    </div>
    <div class="section level2">
    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
    <p>Calculates type-II or type-III analysis-of-variance tables for model objects produced by lm, glm, multinom (in the nnet package), polr (in the MASS package), coxph (in the survival package), coxme (in the coxme pckage), svyglm and svycoxph (in the survey package), rlm (in the MASS package), lmer in the lme4 package, lme in the nlme package, and (by the default method) for most models with a linear predictor and asymptotically normal coefficients (see details below). For linear models, F-tests are calculated; for generalized linear models, likelihood-ratio chisquare, Wald chisquare, or F-tests are calculated; for multinomial logit and proportional-odds logit models, likelihood-ratio tests are calculated. Various test statistics are provided for multivariate linear models produced by lm or manova. Partial-likelihood-ratio tests or Wald tests are provided for Cox models. Wald chi-square tests are provided for fixed effects in linear and generalized linear mixed-effects models. Wald chi-square or F tests are provided in the default case.</p>
    </div>
    <div class="section level2">
    <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2>
    <p>John Fox jfox@mcmaster.ca; the code for the Mauchly test and Greenhouse-Geisser and Huynh-Feldt corrections for non-spericity in repeated-measures ANOVA are adapted from the functions stats:::stats:::mauchly.test.SSD and stats:::sphericity by R Core; summary.Anova.mlm and print.summary.Anova.mlm incorporates code contributed by Gabriel Baud-Bovy.</p>
    </div>

    <div class="section level2">
    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \donttest{</span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">mpg</span> <span class="op">~</span> <span class="va">cyl</span> <span class="op">+</span> <span class="va">disp</span>, data <span class="op">=</span> <span class="va">mtcars</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu">car_Anova</span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Anova Table (Type II tests)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Response: mpg</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>            Sum Sq Df F value  Pr(&gt;F)  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> cyl        46.418  1  4.9720 0.03366 *</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> disp       37.594  1  4.0268 0.05419 .</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Residuals 270.740 29                  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ---</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</span>
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>
    </div>
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