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<meta property="og:description" content="在分析数据集时，常常会碰到一些缺失值，如果缺失值的数量相对总体来说非常小，那么直接删除缺失值就是一种可行的方法。但某些情况下，直接删除缺失值可能会损失一些有用信息，此时就需要寻找方法来补全缺失值。（庄闪闪） 安装包 conda create -n MICE -c conda-forge r-mice -y conda activate MICE conda install -c conda-for">
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            <h1 id="seo-header">使用MICE包对数据缺失值进行插补</h1>
            
            
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                <p>在分析数据集时，常常会碰到一些缺失值，如果缺失值的数量相对总体来说非常小，那么直接删除缺失值就是一种可行的方法。但某些情况下，直接删除缺失值可能会损失一些有用信息，此时就需要寻找方法来补全缺失值。（<a target="_blank" rel="noopener" href="https://cloud.tencent.com/developer/user/8270620">庄闪闪</a>）</p>
<h2 id="安装包"><a href="#安装包" class="headerlink" title="安装包"></a>安装包</h2><ul>
<li>conda create -n MICE -c conda-forge r-mice -y</li>
<li>conda activate MICE</li>
<li>conda install -c conda-forge r-tidyverse -y</li>
<li>conda install -c conda-forge r-irkernel -y</li>
<li>conda install -c conda-forge r-vim -y</li>
<li>Rscript -e “IRkernel::installspec(name&#x3D;’MICE’, displayname&#x3D;’r-MICE’)”</li>
</ul>
<h2 id="导入数据"><a href="#导入数据" class="headerlink" title="导入数据"></a>导入数据</h2><p><a target="_blank" rel="noopener" href="https://occdn.limour.top/2325.html">数据来源</a></p>
<figure class="highlight r"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><code class="hljs R">rppa <span class="hljs-operator">&lt;-</span> readRDS<span class="hljs-punctuation">(</span><span class="hljs-string">&#x27;PRAD_rppa.rds&#x27;</span><span class="hljs-punctuation">)</span><br>pMiss <span class="hljs-operator">&lt;-</span> <span class="hljs-keyword">function</span><span class="hljs-punctuation">(</span>x<span class="hljs-punctuation">)</span><span class="hljs-punctuation">&#123;</span><span class="hljs-built_in">round</span><span class="hljs-punctuation">(</span><span class="hljs-built_in">sum</span><span class="hljs-punctuation">(</span><span class="hljs-built_in">is.na</span><span class="hljs-punctuation">(</span>x<span class="hljs-punctuation">)</span><span class="hljs-punctuation">)</span><span class="hljs-operator">/</span><span class="hljs-built_in">length</span><span class="hljs-punctuation">(</span>x<span class="hljs-punctuation">)</span><span class="hljs-punctuation">,</span><span class="hljs-number">3</span><span class="hljs-punctuation">)</span><span class="hljs-punctuation">&#125;</span><br>rppa <span class="hljs-operator">&lt;-</span> rppa<span class="hljs-punctuation">[</span>apply<span class="hljs-punctuation">(</span>rppa<span class="hljs-punctuation">,</span> <span class="hljs-number">1</span><span class="hljs-punctuation">,</span> pMiss<span class="hljs-punctuation">)</span> <span class="hljs-operator">&lt;</span> <span class="hljs-number">0.05</span><span class="hljs-punctuation">,</span> <span class="hljs-punctuation">]</span><br>rppa <span class="hljs-operator">&lt;-</span> rppa<span class="hljs-punctuation">[</span><span class="hljs-punctuation">,</span> apply<span class="hljs-punctuation">(</span>rppa<span class="hljs-punctuation">,</span> <span class="hljs-number">2</span><span class="hljs-punctuation">,</span> pMiss<span class="hljs-punctuation">)</span> <span class="hljs-operator">&lt;</span> <span class="hljs-number">0.05</span><span class="hljs-punctuation">]</span><br><span class="hljs-built_in">sum</span><span class="hljs-punctuation">(</span><span class="hljs-built_in">is.na</span><span class="hljs-punctuation">(</span>rppa<span class="hljs-punctuation">)</span><span class="hljs-punctuation">)</span><br></code></pre></td></tr></table></figure>

<p>额，好像没有NA了，这一步先不跑，熟悉一下MICE包吧，数据集用airquality</p>
<h2 id="查看数据质量"><a href="#查看数据质量" class="headerlink" title="查看数据质量"></a>查看数据质量</h2><figure class="highlight r"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><code class="hljs R">mice<span class="hljs-operator">::</span>md.pattern<span class="hljs-punctuation">(</span>airquality<span class="hljs-punctuation">)</span><br>VIM<span class="hljs-operator">::</span>aggr<span class="hljs-punctuation">(</span>airquality<span class="hljs-punctuation">,</span> col<span class="hljs-operator">=</span><span class="hljs-built_in">c</span><span class="hljs-punctuation">(</span><span class="hljs-string">&#x27;navyblue&#x27;</span><span class="hljs-punctuation">,</span><span class="hljs-string">&#x27;red&#x27;</span><span class="hljs-punctuation">)</span><span class="hljs-punctuation">,</span> numbers<span class="hljs-operator">=</span><span class="hljs-literal">TRUE</span><span class="hljs-punctuation">,</span> sortVars<span class="hljs-operator">=</span><span class="hljs-literal">TRUE</span><span class="hljs-punctuation">,</span> <br>          labels<span class="hljs-operator">=</span><span class="hljs-built_in">names</span><span class="hljs-punctuation">(</span>airquality<span class="hljs-punctuation">)</span><span class="hljs-punctuation">,</span> cex.axis<span class="hljs-operator">=</span><span class="hljs-number">.7</span><span class="hljs-punctuation">,</span> gap<span class="hljs-operator">=</span><span class="hljs-number">3</span><span class="hljs-punctuation">,</span> <br>          ylab<span class="hljs-operator">=</span><span class="hljs-built_in">c</span><span class="hljs-punctuation">(</span><span class="hljs-string">&quot;Histogram of missing data&quot;</span><span class="hljs-punctuation">,</span><span class="hljs-string">&quot;Pattern&quot;</span><span class="hljs-punctuation">)</span><span class="hljs-punctuation">)</span><br>VIM<span class="hljs-operator">::</span>marginplot<span class="hljs-punctuation">(</span>airquality<span class="hljs-punctuation">[</span><span class="hljs-built_in">c</span><span class="hljs-punctuation">(</span><span class="hljs-number">1</span><span class="hljs-punctuation">,</span><span class="hljs-number">2</span><span class="hljs-punctuation">)</span><span class="hljs-punctuation">]</span><span class="hljs-punctuation">)</span><br></code></pre></td></tr></table></figure>

<h2 id="进行迭代插补"><a href="#进行迭代插补" class="headerlink" title="进行迭代插补"></a>进行迭代插补</h2><figure class="highlight r"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><code class="hljs R">tempData <span class="hljs-operator">&lt;-</span> mice<span class="hljs-operator">::</span>mice<span class="hljs-punctuation">(</span>airquality<span class="hljs-punctuation">,</span>m<span class="hljs-operator">=</span><span class="hljs-number">5</span><span class="hljs-punctuation">,</span>maxit<span class="hljs-operator">=</span><span class="hljs-number">50</span><span class="hljs-punctuation">,</span>meth<span class="hljs-operator">=</span><span class="hljs-string">&#x27;pmm&#x27;</span><span class="hljs-punctuation">,</span>seed<span class="hljs-operator">=</span><span class="hljs-number">1</span><span class="hljs-punctuation">)</span><br><span class="hljs-comment"># meth：指定数据中每一列的输入方法。</span><br><span class="hljs-comment"># 1）数值型数据适用 pmm；</span><br><span class="hljs-comment"># 2）二分类数据适用 logreg；</span><br><span class="hljs-comment"># 3）无序多类别数据适用 ployreg；</span><br><span class="hljs-comment"># 4）有序多分类变量适用 polr。</span><br><span class="hljs-comment"># 默认方法为 pmm </span><br></code></pre></td></tr></table></figure>

<h2 id="选择合适的插补"><a href="#选择合适的插补" class="headerlink" title="选择合适的插补"></a>选择合适的插补</h2><figure class="highlight r"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><code class="hljs R">mice<span class="hljs-operator">::</span>densityplot<span class="hljs-punctuation">(</span>tempData<span class="hljs-punctuation">,</span><span class="hljs-operator">~</span> Ozone <span class="hljs-operator">+</span> Solar.R  .imp<span class="hljs-punctuation">)</span><br><span class="hljs-comment"># 蓝色为原始数据的分布，第一幅红色图为一重插补，以此类推，选择最符合的</span><br>mice<span class="hljs-operator">::</span>densityplot<span class="hljs-punctuation">(</span>tempData<span class="hljs-punctuation">,</span> <span class="hljs-operator">~</span> Ozone <span class="hljs-operator">+</span> Solar.R .imp <span class="hljs-operator">==</span> <span class="hljs-number">4</span><span class="hljs-punctuation">)</span><br></code></pre></td></tr></table></figure>

<h2 id="导出插补后的数据"><a href="#导出插补后的数据" class="headerlink" title="导出插补后的数据"></a>导出插补后的数据</h2><figure class="highlight r"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><code class="hljs R">Data <span class="hljs-operator">&lt;-</span> mice<span class="hljs-operator">::</span>complete<span class="hljs-punctuation">(</span>tempData<span class="hljs-punctuation">,</span> action <span class="hljs-operator">=</span> <span class="hljs-number">4</span><span class="hljs-punctuation">)</span><br><span class="hljs-comment"># action的参数值表示选择第几重的插补值来填补原始数据集，根据前面的图来选择</span><br></code></pre></td></tr></table></figure>
                
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