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<title>Moderated Statistical Tests for Influence Functions — modtest_ic • biotmle</title>


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<meta property="og:title" content="Moderated Statistical Tests for Influence Functions — modtest_ic" />
<meta property="og:description" content="Performs variance shrinkage via application of an empirical Bayes procedure
(of LIMMA) on the observed data after a transformation moving the data to
influence function space, based on the average treatment effect parameter." />




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    <h1>Moderated Statistical Tests for Influence Functions</h1>
    <small class="dont-index">Source: <a href='https://github.com/nhejazi/biotmle/blob/master/R/eif_moderated.R'><code>R/eif_moderated.R</code></a></small>
    <div class="hidden name"><code>modtest_ic.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Performs variance shrinkage via application of an empirical Bayes procedure
(of LIMMA) on the observed data after a transformation moving the data to
influence function space, based on the average treatment effect parameter.</p>
    </div>

    <pre class="usage"><span class='fu'>modtest_ic</span><span class='op'>(</span><span class='va'>biotmle</span>, adjust <span class='op'>=</span> <span class='st'>"BH"</span>, pval_type <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"normal"</span>, <span class='st'>"logistic"</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span></pre>

    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
    <table class="ref-arguments">
    <colgroup><col class="name" /><col class="desc" /></colgroup>
    <tr>
      <th>biotmle</th>
      <td><p><code>biotmle</code> object as generated by <code>biomarkertmle</code></p></td>
    </tr>
    <tr>
      <th>adjust</th>
      <td><p>the multiple testing correction to be applied to p-values that
are generated from the moderated tests. The recommended (default) method
is that of Benjamini and Hochberg. See <a href='https://rdrr.io/pkg/limma/man/toptable.html'>topTable</a> for a list of
appropriate methods.</p></td>
    </tr>
    <tr>
      <th>pval_type</th>
      <td><p>The reference distribution to be used for computing the
p-value. Those based on the normal approximation tend to provide misleading
inference when working with moderately sized (finite) samples. Use of the
logistic distribution has been found to empirically improve performance in
settings where multiple hypothesis testing is a concern.</p></td>
    </tr>
    <tr>
      <th>...</th>
      <td><p>Other arguments passed to <code><a href='https://rdrr.io/pkg/limma/man/toptable.html'>topTable</a></code>.</p></td>
    </tr>
    </table>

    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>

    <p><code>biotmle</code> object containing the results of applying both
 <code><a href='https://rdrr.io/pkg/limma/man/lmFit.html'>lmFit</a></code> and <code><a href='https://rdrr.io/pkg/limma/man/toptable.html'>topTable</a></code>.</p>

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://dplyr.tidyverse.org'>dplyr</a></span><span class='op'>)</span>
<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'>biotmleData</span><span class='op'>)</span>
<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://github.com/ecpolley/SuperLearner'>SuperLearner</a></span><span class='op'>)</span>
<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://bioconductor.org/packages/SummarizedExperiment'>SummarizedExperiment</a></span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/utils/data.html'>data</a></span><span class='op'>(</span><span class='va'>illuminaData</span><span class='op'>)</span>

<span class='fu'><a href='https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html'>colData</a></span><span class='op'>(</span><span class='va'>illuminaData</span><span class='op'>)</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html'>colData</a></span><span class='op'>(</span><span class='va'>illuminaData</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
  <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
  <span class='fu'>dplyr</span><span class='fu'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span><span class='op'>(</span>age <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span><span class='op'>(</span><span class='va'>age</span> <span class='op'>&gt;</span> <span class='fu'><a href='https://rdrr.io/r/stats/median.html'>median</a></span><span class='op'>(</span><span class='va'>age</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
  <span class='fu'>DataFrame</span><span class='op'>(</span><span class='op'>)</span>
<span class='va'>benz_idx</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/which.html'>which</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html'>colData</a></span><span class='op'>(</span><span class='va'>illuminaData</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%in%</span> <span class='st'>"benzene"</span><span class='op'>)</span>

<span class='va'>biomarkerTMLEout</span> <span class='op'>&lt;-</span> <span class='fu'><a href='biomarkertmle.html'>biomarkertmle</a></span><span class='op'>(</span>
  se <span class='op'>=</span> <span class='va'>illuminaData</span><span class='op'>[</span><span class='fl'>1</span><span class='op'>:</span><span class='fl'>2</span>, <span class='op'>]</span>,
  varInt <span class='op'>=</span> <span class='va'>benz_idx</span>,
  bppar_type <span class='op'>=</span> <span class='fu'>BiocParallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/pkg/BiocParallel/man/SerialParam-class.html'>SerialParam</a></span><span class='op'>(</span><span class='op'>)</span>,
  g_lib <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SL.mean"</span>, <span class='st'>"SL.glm"</span><span class='op'>)</span>,
  Q_lib <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SL.mean"</span>, <span class='st'>"SL.glm"</span><span class='op'>)</span>
<span class='op'>)</span>
</div><div class='output co'>#&gt; 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 100%
#&gt; </div><div class='input'>
<span class='va'>limmaTMLEout</span> <span class='op'>&lt;-</span> <span class='fu'>modtest_ic</span><span class='op'>(</span>biotmle <span class='op'>=</span> <span class='va'>biomarkerTMLEout</span><span class='op'>)</span>
</div></pre>
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