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(v0.8.0.9037) complete documentation rewrite

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dr. M.S. (Matthijs) Berends
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<script src="../extra.js"></script>
<meta property="og:title" content="<em>G</em>-test for Count Data — g.test" />
<meta property="og:description" content="g.test() performs chi-squared contingency table tests and goodness-of-fit tests, just like chisq.test() but is more reliable 1. A G-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a G-test of goodness-of-fit), or to see whether the proportions of one variable are different for different values of the other variable (called a G-test of independence)." />
<meta property="og:description" content="g.test() performs chi-squared contingency table tests and goodness-of-fit tests, just like chisq.test() but is more reliable (1). A G-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a G-test of goodness-of-fit), or to see whether the proportions of one variable are different for different values of the other variable (called a G-test of independence)." />
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.png" />
<meta name="twitter:card" content="summary" />
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9036</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9037</span>
</span>
</div>
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</div>
<div class="ref-description">
<p><code>g.test()</code> performs chi-squared contingency table tests and goodness-of-fit tests, just like <code><a href='https://rdrr.io/r/stats/chisq.test.html'>chisq.test()</a></code> but is more reliable 1. A <em>G</em>-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a <strong><em>G</em>-test of goodness-of-fit</strong>), or to see whether the proportions of one variable are different for different values of the other variable (called a <strong><em>G</em>-test of independence</strong>).</p>
<p><code>g.test()</code> performs chi-squared contingency table tests and goodness-of-fit tests, just like <code><a href='https://rdrr.io/r/stats/chisq.test.html'>chisq.test()</a></code> but is more reliable (1). A <em>G</em>-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a <strong><em>G</em>-test of goodness-of-fit</strong>), or to see whether the proportions of one variable are different for different values of the other variable (called a <strong><em>G</em>-test of independence</strong>).</p>
</div>
<pre class="usage"><span class='fu'>g.test</span>(<span class='no'>x</span>, <span class='kw'>y</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='fl'>1</span>/<span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span>(<span class='no'>x</span>), <span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span>(<span class='no'>x</span>)), <span class='kw'>rescale.p</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
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<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
<p>1 McDonald, J.H. 2014. <strong>Handbook of Biological Statistics (3rd ed.)</strong>. Sparky House Publishing, Baltimore, Maryland. <a href='http://www.biostathandbook.com/gtestgof.html'>http://www.biostathandbook.com/gtestgof.html</a>.</p>
<ol>
<li><p>McDonald, J.H. 2014. <strong>Handbook of Biological Statistics (3rd ed.)</strong>. Sparky House Publishing, Baltimore, Maryland. <a href='http://www.biostathandbook.com/gtestgof.html'>http://www.biostathandbook.com/gtestgof.html</a>.</p></li>
</ol>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='https://rdrr.io/r/stats/chisq.test.html'>chisq.test()</a></code></p></div>