[85ff8e]: / docs / reference / modtest_ic.html

Download this file

223 lines (172 with data), 13.1 kB

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
<!-- Generated by pkgdown: do not edit by hand -->
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Moderated Statistical Tests for Influence Functions — modtest_ic • biotmle</title>
<!-- jquery -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
<!-- Bootstrap -->
<link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/readable/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
<!-- bootstrap-toc -->
<link rel="stylesheet" href="../bootstrap-toc.css">
<script src="../bootstrap-toc.js"></script>
<!-- Font Awesome icons -->
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
<!-- clipboard.js -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
<!-- headroom.js -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
<!-- pkgdown -->
<link href="../pkgdown.css" rel="stylesheet">
<script src="../pkgdown.js"></script>
<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." />
<!-- mathjax -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
<!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]-->
</head>
<body data-spy="scroll" data-target="#toc">
<div class="container template-reference-topic">
<header>
<div class="navbar navbar-default navbar-fixed-top" role="navigation">
<div class="container">
<div class="navbar-header">
<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
<span class="sr-only">Toggle navigation</span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">biotmle</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.17.0</span>
</span>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="../index.html">
<span class="fas fa-home fa-lg"></span>
</a>
</li>
<li>
<a href="../reference/index.html">Reference</a>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
Articles
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="../articles/exposureBiomarkers.html">Identifying Biomarkers from an Exposure Variable with `biotmle`</a>
</li>
</ul>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://github.com/nhejazi/biotmle/">
<span class="fab fa-github fa-lg"></span>
</a>
</li>
</ul>
</div><!--/.nav-collapse -->
</div><!--/.container -->
</div><!--/.navbar -->
</header>
<div class="row">
<div class="col-md-9 contents">
<div class="page-header">
<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>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">
<h2 data-toc-skip>Contents</h2>
</nav>
</div>
</div>
<footer>
<div class="copyright">
<p>Developed by Nima Hejazi, Alan Hubbard, Mark van der Laan.</p>
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>
</div>
</body>
</html>