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<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a regression model programatically — regression_model • FreesearchR</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Montserrat-0.4.10/font.css" rel="stylesheet"><link href="../deps/Public_Sans-0.4.10/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Create a regression model programatically — regression_model"><meta name="description" content="Output is a concatenated list of model information and model"><meta property="og:description" content="Output is a concatenated list of model information and model"><meta property="og:image" content="https://agdamsbo.github.io/FreesearchR/logo.png"><script defer src="https://stats.freesearchr.org/script.js" data-website-id="85bfd1e8-2cbe-4a4a-aa34-1dfb2960905b"></script></head><body>
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<img src="../logo.png" class="logo" alt=""><h1>Create a regression model programatically</h1>
<small class="dont-index">Source: <a href="https://github.com/agdamsbo/FreesearchR/blob/main/R/regression_model.R" class="external-link"><code>R/regression_model.R</code></a></small>
<div class="d-none name"><code>regression_model.Rd</code></div>
</div>
<div class="ref-description section level2">
<p>Output is a concatenated list of model information and model</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">regression_model</span><span class="op">(</span></span>
<span> <span class="va">data</span>,</span>
<span> outcome.str <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> auto.mode <span class="op">=</span> <span class="cn">FALSE</span>,</span>
<span> formula.str <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> args.list <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> fun <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> vars <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> <span class="va">...</span></span>
<span><span class="op">)</span></span>
<span></span>
<span><span class="fu">regression_model_uv</span><span class="op">(</span></span>
<span> <span class="va">data</span>,</span>
<span> <span class="va">outcome.str</span>,</span>
<span> args.list <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> fun <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> vars <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> <span class="va">...</span></span>
<span><span class="op">)</span></span>
<span></span>
<span><span class="fu">regression_model_list</span><span class="op">(</span></span>
<span> <span class="va">data</span>,</span>
<span> <span class="va">outcome.str</span>,</span>
<span> <span class="va">fun.descr</span>,</span>
<span> fun <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> formula.str <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> args.list <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> vars <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> <span class="va">...</span></span>
<span><span class="op">)</span></span>
<span></span>
<span><span class="fu">regression_model_uv_list</span><span class="op">(</span></span>
<span> <span class="va">data</span>,</span>
<span> <span class="va">outcome.str</span>,</span>
<span> <span class="va">fun.descr</span>,</span>
<span> fun <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> formula.str <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> args.list <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> vars <span class="op">=</span> <span class="cn">NULL</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 id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
<dd><p>data</p></dd>
<dt id="arg-outcome-str">outcome.str<a class="anchor" aria-label="anchor" href="#arg-outcome-str"></a></dt>
<dd><p>name of outcome variable</p></dd>
<dt id="arg-auto-mode">auto.mode<a class="anchor" aria-label="anchor" href="#arg-auto-mode"></a></dt>
<dd><p>Make assumptions on function dependent on outcome data format. Overwrites other arguments.</p></dd>
<dt id="arg-formula-str">formula.str<a class="anchor" aria-label="anchor" href="#arg-formula-str"></a></dt>
<dd><p>custom formula glue string. Default is NULL.</p></dd>
<dt id="arg-args-list">args.list<a class="anchor" aria-label="anchor" href="#arg-args-list"></a></dt>
<dd><p>custom character string to be converted using
argsstring2list() or list of arguments. Default is NULL.</p></dd>
<dt id="arg-fun">fun<a class="anchor" aria-label="anchor" href="#arg-fun"></a></dt>
<dd><p>name of custom function. Default is NULL.</p></dd>
<dt id="arg-vars">vars<a class="anchor" aria-label="anchor" href="#arg-vars"></a></dt>
<dd><p>character vector of variables to include</p></dd>
<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>ignored</p></dd>
<dt id="arg-fun-descr">fun.descr<a class="anchor" aria-label="anchor" href="#arg-fun-descr"></a></dt>
<dd><p>Description of chosen function matching description in
"supported_functions()"</p></dd>
</dl></div>
<div class="section level2">
<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
<p>object of standard class for fun</p>
<p>object of standard class for fun</p>
<p>list</p>
<p>list</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="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span>outcome.str <span class="op">=</span> <span class="st">"age"</span><span class="op">)</span></span></span>
<span class="r-err co"><span class="r-pr">#&gt;</span> <span class="error">Error in str2lang(x):</span> &lt;text&gt;:2:0: unexpected end of input</span>
<span class="r-err co"><span class="r-pr">#&gt;</span> 1: age~</span>
<span class="r-err co"><span class="r-pr">#&gt;</span> ^</span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"age"</span>,</span></span>
<span class="r-in"><span> auto.mode <span class="op">=</span> <span class="cn">FALSE</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::lm"</span>,</span></span>
<span class="r-in"><span> formula.str <span class="op">=</span> <span class="st">"{outcome.str}~."</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="cn">NULL</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Call:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> (function (formula, data, subset, weights, na.action, method = "qr", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> contrasts = NULL, offset, ...) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> {</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ret.x &lt;- x</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ret.y &lt;- y</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> cl &lt;- match.call()</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mf &lt;- match.call(expand.dots = FALSE)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> m &lt;- match(c("formula", "data", "subset", "weights", "na.action", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> "offset"), names(mf), 0L)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mf &lt;- mf[c(1L, m)]</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mf$drop.unused.levels &lt;- TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mf[[1L]] &lt;- quote(stats::model.frame)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mf &lt;- eval(mf, parent.frame())</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (method == "model.frame") </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> return(mf)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> else if (method != "qr") </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> warning(gettextf("method = '%s' is not supported. Using 'qr'", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> method), domain = NA)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mt &lt;- attr(mf, "terms")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> y &lt;- model.response(mf, "numeric")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> w &lt;- as.vector(model.weights(mf))</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (!is.null(w) &amp;&amp; !is.numeric(w)) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> stop("'weights' must be a numeric vector")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> offset &lt;- model.offset(mf)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mlm &lt;- is.matrix(y)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ny &lt;- if (mlm) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> nrow(y)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> else length(y)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (!is.null(offset)) {</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (!mlm) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> offset &lt;- as.vector(offset)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (NROW(offset) != ny) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> stop(gettextf("number of offsets is %d, should equal %d (number of observations)", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> NROW(offset), ny), domain = NA)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> }</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (is.empty.model(mt)) {</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> x &lt;- NULL</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z &lt;- list(coefficients = if (mlm) matrix(NA_real_, 0, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ncol(y)) else numeric(), residuals = y, fitted.values = 0 * </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> y, weights = w, rank = 0L, df.residual = if (!is.null(w)) sum(w != </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0) else ny)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (!is.null(offset)) {</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$fitted.values &lt;- offset</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$residuals &lt;- y - offset</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> }</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> }</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> else {</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> x &lt;- model.matrix(mt, mf, contrasts)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z &lt;- if (is.null(w)) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> lm.fit(x, y, offset = offset, singular.ok = singular.ok, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ...)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> else lm.wfit(x, y, w, offset = offset, singular.ok = singular.ok, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ...)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> }</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> class(z) &lt;- c(if (mlm) "mlm", "lm")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$na.action &lt;- attr(mf, "na.action")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$offset &lt;- offset</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$contrasts &lt;- attr(x, "contrasts")</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$xlevels &lt;- .getXlevels(mt, mf)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$call &lt;- cl</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$terms &lt;- mt</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (model) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$model &lt;- mf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (ret.x) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$x &lt;- x</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (ret.y) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$y &lt;- y</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> if (!qr) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z$qr &lt;- NULL</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> z</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> })(formula = age ~ ., data = structure(list(trt = structure(c(1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 1L, 2L, 1L, 1L, 1L, 1L), levels = c("Drug A", "Drug B"), class = "factor", label = "Chemotherapy Treatment"), </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> age = structure(c(23, 9, 31, NA, 51, 39, 37, 32, 31, 34, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 42, 63, 54, 21, 48, 71, 38, 49, 57, 46, 47, 52, 61, 38, 34, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 49, 63, 67, 68, 78, 36, 37, 53, 36, 51, 48, 57, 31, 37, 28, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 40, 49, 61, 56, 54, 71, 38, 31, 48, NA, 83, 52, 32, 53, 69, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 60, 45, 39, NA, 38, 36, 71, 31, 43, 57, 53, 25, 44, 25, 30, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 51, 40, NA, 43, 21, 54, 67, 43, 54, 41, 34, 34, 6, 39, 36, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 58, 27, 47, NA, 50, 61, 47, 52, 51, 68, 33, 65, 34, 38, 60, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10, 49, 56, 50, 60, 49, 54, 39, 48, 65, 47, 61, 34, NA, NA, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 58, 26, 44, 17, 68, 57, 66, 44, NA, 67, 48, 62, 35, 53, 53, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 66, 55, 57, 47, 58, 43, 45, 44, 63, 59, 44, 53, 51, 28, 65, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 63, 76, 61, 33, 48, 42, 36, 55, 20, 26, 50, 47, 74, 50, 31, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 45, 51, 66, 76, 47, 48, 56, 70, 46, 43, 41, 41, 19, 49, 43, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 43, 75, 52, 42, 37, 45, 35, 67, 38, 44, 45, 39, 46, NA, 42, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 60, 31, 45, 38, NA, 19, 69, 66, NA, 64), label = "Age"), </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> marker = structure(c(0.16, 1.107, 0.277, 2.067, 2.767, 0.613, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.354, 1.739, 0.144, 0.205, 0.513, 0.06, 0.831, 0.258, 0.128, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.445, 2.083, 0.157, 0.066, 0.325, 0.266, 0.719, 1.713, 0.096, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.105, 0.043, 0.981, 1.156, 0.105, 0.175, 0.309, 1.869, 2.008, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1.894, 0.16, 1.209, 0.108, 0.611, 0.222, 0.803, 0.37, NA, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.177, 1.479, 0.161, 0.737, 0.124, 0.092, 0.385, 0.21, 0.475, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1.628, 0.583, NA, 0.702, 1.206, 2.213, 1.406, 0.101, 0.013, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2.032, 1.046, 0.408, 2.636, 1.263, NA, 2.447, 1.041, 0.531, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.924, 1.087, 0.733, 2.157, 0.333, 1.527, 2.238, 0.153, 0.305, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.131, 0.386, 1.645, 1.321, 0.229, 0.615, 1.976, 1.941, 0.22, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3.874, 0.982, 1.68, 1.091, 0.169, 0.511, 2.141, 0.599, NA, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.389, 0.005, 0.075, 1.491, 0.358, 1.709, 0.056, 1.354, 2.522, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.387, 0.592, 0.243, 0.215, 1.207, 0.29, 0.718, 0.589, 0.003, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1.328, 0.308, 0.691, 3.249, 0.039, 1.804, 0.238, 2.702, 1.441, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.27, NA, NA, 0.062, 2.19, 0.976, 3.062, 0.124, 0.045, 1.892, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.711, 1.079, 1.061, 0.239, 0.361, 0.033, 1.133, 1.225, 1.418, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3.751, 3.02, 0.086, 0.772, 1.882, 2.725, 2.41, 0.352, 0.895, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.215, 0.141, 2.288, 1.658, 1.255, 1.306, 0.081, 0.667, 0.046, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.662, 1.985, 1.063, 1.55, 0.015, 0.056, NA, 0.51, 0.929, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2.345, 0.25, 0.816, 0.022, 0.16, 0.547, 3.642, 0.092, 1.2, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1.512, 2.124, NA, 0.862, 0.182, 1.075, 0.021, 0.402, 0.063, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1.129, 0.61, NA, 0.717, 0.205, 0.946, 0.386, 0.37, 1.148, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> NA, 0.136, 0.439, 1.148), label = "Marker Level (ng/mL)"), </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> stage = structure(c(1L, 2L, 1L, 3L, 4L, 4L, 1L, 1L, 1L, 3L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 3L, 4L, 4L, 1L, 4L, 4L, 2L, 1L, 1L, 2L, 2L, 4L, 4L, 4L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 4L, 1L, 4L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 4L, 4L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 1L, 4L, 3L, 4L, 1L, 1L, 2L, 1L, 4L, 1L, 2L, 2L, 3L, 3L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 4L, 1L, 4L, 2L, 4L, 1L, 4L, 1L, 4L, 1L, 1L, 1L, 4L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 1L, 4L, 4L, 2L, 2L, 4L, 4L, 3L, 2L, 4L, 3L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4L, 1L, 2L, 1L, 4L, 3L, 3L, 1L, 3L, 2L, 3L, 2L, 2L, 3L, 4L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4L, 3L, 3L, 2L, 3L, 2L, 2L, 3L, 2L, 1L, 1L, 3L, 4L, 1L, 4L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 3L, 2L, 4L, 2L, 1L, 2L, 1L, 4L, 3L, 3L, 3L, 2L, 1L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 2L, 2L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 3L, 4L, 1L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 3L, 4L, 2L, 4L, 2L, 1L, 2L, 3L, 1L, 3L, 4L, 2L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 3L, 1L, 2L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 1L, 2L, 4L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 4L, 4L, 2L, 3L, 4L, 3L, 4L, 4L, 1L, 1L, 4L, 4L, 4L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 4L, 3L, 3L, 2L, 2L, 4L, 3L), levels = c("T1", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> "T2", "T3", "T4"), class = "factor", label = "T Stage"), </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> grade = structure(c(2L, 1L, 2L, 3L, 3L, 1L, 2L, 1L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 1L, 3L, 1L, 1L, 3L, 3L, 2L, 3L, 2L, 1L, 2L, 1L, 1L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 2L, 2L, 2L, 1L, 3L, 2L, 1L, 1L, 1L, 3L, 2L, 2L, 3L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 3L, 3L, 1L, 3L, 1L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 3L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 3L, 3L, 3L, 2L, 3L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 3L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 1L, 2L, 2L, 1L, 2L, 2L, 3L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 3L, 2L, 1L, 3L, 2L, 1L, 2L, 2L, 2L, 1L, 3L, 3L, 2L, 3L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2L, 2L, 2L, 2L, 1L, 1L, 3L, 2L, 2L, 1L, 2L, 1L, 2L, 3L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 1L, 3L, 1L, 1L, 2L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 1L, 2L, 1L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 2L, 3L, 2L, 2L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3L, 2L, 3L, 3L, 2L, 1L, 2L, 3L, 3L, 1L), levels = c("I", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> "II", "III"), class = "factor", label = "Grade"), response = structure(c(0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 1L, 0L, NA, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 0L, NA, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, 0L, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, NA, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, NA, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, NA, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 0L, 0L), label = "Tumor Response"), death = structure(c(0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1L, 0L, 1L, 0L), label = "Patient Died"), ttdeath = structure(c(24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 24, 17.64, 16.43, 15.64, 24, 18.43, 24, 10.53, 24, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 14.34, 12.89, 22.68, 8.71, 24, 15.21, 24, 24, 24, 24, 16.92, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 23.89, 6.32, 15.77, 24, 24, 15.45, 17.43, 24, 20.9, 24, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 21.19, 12.52, 24, 15.59, 18, 18.02, 12.43, 12.1, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 17.42, 24, 24, 24, 12.19, 10.02, 18.23, 10.42, 24, 24, 19.34, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 12.21, 14.46, 19.34, 10.16, 13.15, 10.12, 24, 22.77, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 22.13, 24, 20.62, 23.23, 7.38, 24, 24, 24, 24, 24, 19.22, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7.27, 23.88, 16.23, 24, 14.06, 24, 24, 24, 16.44, 23.81, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 18.37, 11.44, 20.94, 5.33, 22.92, 10.33, 24, 24, 14.54, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 19.14, 24, 21.19, 16.07, 9.97, 24, 24, 24, 19.75, 16.67, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 11.18, 18.29, 24, 17.56, 17.45, 24, 22.86, 13.68, 24, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 17.46, 24, 24, 24, 24, 24, 13, 9.73, 15.65, 24, 3.53, 20.35, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 23.41, 16.47, 24, 24, 14.65, 17.81, 24, 21.83, 24, 24, 21.49, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 12.68, 24, 24, 24, 24, 10.07, 24, 24, 24, 8.37, 20.33, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 21.33, 12.63, 13.08, 24, 15.1, 20.14, 10.55, 24, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 24, 23.6, 24, 19.98, 15.55, 23.72, 22.41, 19.54, 16.57, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 24, 24, 21.91, 24, 12.53, 24, 18.63, 14.82, 16.46, 24, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9.24, 17.77, 24, 24, 9.92, 16.16, 10.51, 20.81, 24, 16.44, </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 24, 22.4, 11.76, 24, 21.6, 24, 19.81, 24), label = "Months to Death/Censor")), class = c("tbl_df", </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> "tbl", "data.frame"), row.names = c(NA, -200L)))</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Coefficients:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> (Intercept) trtDrug B marker stageT2 stageT3 stageT4 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 45.9247 -0.4052 -0.1435 2.0519 2.4437 -3.1573 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> gradeII gradeIII response death ttdeath </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 0.1750 1.6855 4.9885 3.0775 -0.1394 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"trt"</span>,</span></span>
<span class="r-in"><span> auto.mode <span class="op">=</span> <span class="cn">FALSE</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::glm"</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>family <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/family.html" class="external-link">binomial</a></span><span class="op">(</span>link <span class="op">=</span> <span class="st">"logit"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-err co"><span class="r-pr">#&gt;</span> <span class="error">Error in str2lang(x):</span> &lt;text&gt;:2:0: unexpected end of input</span>
<span class="r-err co"><span class="r-pr">#&gt;</span> 1: trt~</span>
<span class="r-err co"><span class="r-pr">#&gt;</span> ^</span>
<span class="r-in"><span><span class="va">m</span> <span class="op">&lt;-</span> <span class="va">mtcars</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"mpg"</span>,</span></span>
<span class="r-in"><span> auto.mode <span class="op">=</span> <span class="cn">FALSE</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::lm"</span>,</span></span>
<span class="r-in"><span> formula.str <span class="op">=</span> <span class="st">"{outcome.str}~{paste(vars,collapse='+')}"</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="cn">NULL</span>,</span></span>
<span class="r-in"><span> vars <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">"mpg"</span>, <span class="st">"cyl"</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>the response appeared on the right-hand side and was dropped</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>problem with term 1 in model.matrix: no columns are assigned</span>
<span class="r-in"><span><span class="fu">broom</span><span class="fu">::</span><span class="fu"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></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> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> term estimate std.error statistic p.value</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> (Intercept) 26.7 0.972 27.4 2.69<span style="color: #949494;">e</span><span style="color: #BB0000;">-22</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> cyl6 -<span style="color: #BB0000;">6.92</span> 1.56 -<span style="color: #BB0000;">4.44</span> 1.19<span style="color: #949494;">e</span><span style="color: #BB0000;">- 4</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> cyl8 -<span style="color: #BB0000;">11.6</span> 1.30 -<span style="color: #BB0000;">8.90</span> 8.57<span style="color: #949494;">e</span><span style="color: #BB0000;">-10</span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model_uv</span><span class="op">(</span>outcome.str <span class="op">=</span> <span class="st">"age"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model_uv</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"age"</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::lm"</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="cn">NULL</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span> <span class="fu">regression_model_uv</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"trt"</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::glm"</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>family <span class="op">=</span> <span class="fu">stats</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/stats/family.html" class="external-link">binomial</a></span><span class="op">(</span>link <span class="op">=</span> <span class="st">"logit"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">m</span>, <span class="fu">broom</span><span class="fu">::</span><span class="va"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></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/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"age"</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::lm"</span>,</span></span>
<span class="r-in"><span> formula.str <span class="op">=</span> <span class="st">"{outcome.str}~."</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="cn">NULL</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">ls</span> <span class="op">&lt;-</span> <span class="fu">regression_model_list</span><span class="op">(</span>data <span class="op">=</span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="va">mtcars</span><span class="op">)</span>, outcome.str <span class="op">=</span> <span class="st">"cyl"</span>, fun.descr <span class="op">=</span> <span class="st">"Ordinal logistic regression model"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">ls</span><span class="op">$</span><span class="va">model</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">ls</span> <span class="op">&lt;-</span> <span class="fu">regression_model_list</span><span class="op">(</span>data <span class="op">=</span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="va">mtcars</span><span class="op">)</span>, outcome.str <span class="op">=</span> <span class="st">"mpg"</span>, fun.descr <span class="op">=</span> <span class="st">"Linear regression model"</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">ls</span> <span class="op">&lt;-</span> <span class="fu">regression_model_list</span><span class="op">(</span>data <span class="op">=</span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span><span class="op">)</span>, outcome.str <span class="op">=</span> <span class="st">"trt"</span>, fun.descr <span class="op">=</span> <span class="st">"Logistic regression model"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">tbl</span> <span class="op">&lt;-</span> <span class="fu">gtsummary</span><span class="fu">::</span><span class="fu"><a href="https://www.danieldsjoberg.com/gtsummary/reference/tbl_regression.html" class="external-link">tbl_regression</a></span><span class="op">(</span><span class="va">ls</span><span class="op">$</span><span class="va">model</span>, exponentiate <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"trt"</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::glm"</span>,</span></span>
<span class="r-in"><span> formula.str <span class="op">=</span> <span class="st">"{outcome.str}~."</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>family <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">tbl2</span> <span class="op">&lt;-</span> <span class="fu">gtsummary</span><span class="fu">::</span><span class="fu"><a href="https://www.danieldsjoberg.com/gtsummary/reference/tbl_regression.html" class="external-link">tbl_regression</a></span><span class="op">(</span><span class="va">m</span>, exponentiate <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu">broom</span><span class="fu">::</span><span class="fu"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></span><span class="op">(</span><span class="va">ls</span><span class="op">$</span><span class="va">model</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu">broom</span><span class="fu">::</span><span class="fu"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
<span class="r-in"><span><span class="fu">gtsummary</span><span class="fu">::</span><span class="va"><a href="https://www.danieldsjoberg.com/gtsummary/reference/trial.html" class="external-link">trial</a></span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">regression_model_uv</span><span class="op">(</span></span></span>
<span class="r-in"><span> outcome.str <span class="op">=</span> <span class="st">"trt"</span>,</span></span>
<span class="r-in"><span> fun <span class="op">=</span> <span class="st">"stats::glm"</span>,</span></span>
<span class="r-in"><span> args.list <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>family <span class="op">=</span> <span class="fu">stats</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/stats/family.html" class="external-link">binomial</a></span><span class="op">(</span>link <span class="op">=</span> <span class="st">"logit"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fu">broom</span><span class="fu">::</span><span class="va"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
<span class="r-in"><span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">ms</span> <span class="op">&lt;-</span> <span class="fu">regression_model_uv_list</span><span class="op">(</span>data <span class="op">=</span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="va">mtcars</span><span class="op">)</span>, outcome.str <span class="op">=</span> <span class="st">"mpg"</span>, fun.descr <span class="op">=</span> <span class="st">"Linear regression model"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">ms</span><span class="op">$</span><span class="va">code</span></span></span>
<span class="r-in"><span><span class="va">ls</span> <span class="op">&lt;-</span> <span class="fu">regression_model_uv_list</span><span class="op">(</span>data <span class="op">=</span> <span class="fu"><a href="default_parsing.html">default_parsing</a></span><span class="op">(</span><span class="va">mtcars</span><span class="op">)</span>, outcome.str <span class="op">=</span> <span class="st">"am"</span>, fun.descr <span class="op">=</span> <span class="st">"Logistic regression model"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">ls</span><span class="op">$</span><span class="va">code</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ms</span><span class="op">$</span><span class="va">model</span>, <span class="fu">broom</span><span class="fu">::</span><span class="va"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></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/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
</code></pre></div>
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