|
|
<!-- 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>Lack-of-fit test for models fitted to data with replicates — loftest • mkin</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 rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" 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="Lack-of-fit test for models fitted to data with replicates — loftest" />
<meta property="og:description" content="This is a generic function with a method currently only defined for mkinfit
objects. It fits an anova model to the data contained in the object and
compares the likelihoods using the likelihood ratio test
lrtest.default from the lmtest package." />
<!-- 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">mkin</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.3</span>
</span>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="../reference/index.html">Functions and data</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/mkin.html">Introduction to mkin</a>
</li>
<li>
<a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a>
</li>
<li>
<a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a>
</li>
<li>
<a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a>
</li>
<li>
<a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a>
</li>
<li>
<a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a>
</li>
<li>
<a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a>
</li>
<li>
<a href="../articles/web_only/benchmarks.html">Some benchmark timings</a>
</li>
</ul>
</li>
<li>
<a href="../news/index.html">News</a>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://github.com/jranke/mkin/">
<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>Lack-of-fit test for models fitted to data with replicates</h1>
<small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/loftest.R'><code>R/loftest.R</code></a></small>
<div class="hidden name"><code>loftest.Rd</code></div>
</div>
<div class="ref-description">
<p>This is a generic function with a method currently only defined for mkinfit
objects. It fits an anova model to the data contained in the object and
compares the likelihoods using the likelihood ratio test
<code><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest.default</a></code> from the lmtest package.</p>
</div>
<pre class="usage"><span class='fu'>loftest</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='co'># S3 method for mkinfit</span>
<span class='fu'>loftest</span><span class='op'>(</span><span class='va'>object</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>object</th>
<td><p>A model object with a defined loftest method</p></td>
</tr>
<tr>
<th>...</th>
<td><p>Not used</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The anova model is interpreted as the simplest form of an mkinfit model,
assuming only a constant variance about the means, but not enforcing any
structure of the means, so we have one model parameter for every mean
of replicate samples.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>lrtest</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># \dontrun{</span>
<span class='va'>test_data</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>synthetic_data_for_UBA_2014</span><span class='op'>[[</span><span class='fl'>12</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>data</span>, <span class='va'>name</span> <span class='op'>==</span> <span class='st'>"parent"</span><span class='op'>)</span>
<span class='va'>sfo_fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>test_data</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span><span class='op'>(</span><span class='va'>sfo_fit</span><span class='op'>)</span> <span class='co'># We see a clear pattern in the residuals</span>
</div><div class='img'><img src='loftest-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>loftest</span><span class='op'>(</span><span class='va'>sfo_fit</span><span class='op'>)</span> <span class='co'># We have a clear lack of fit</span>
</div><div class='output co'>#> Likelihood ratio test
#>
#> Model 1: ANOVA with error model const
#> Model 2: SFO with error model const
#> #Df LogLik Df Chisq Pr(>Chisq)
#> 1 10 -40.710
#> 2 3 -63.954 -7 46.487 7.027e-08 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'>#</span>
<span class='co'># We try a different model (the one that was used to generate the data)</span>
<span class='va'>dfop_fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='va'>test_data</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span><span class='op'>(</span><span class='va'>dfop_fit</span><span class='op'>)</span> <span class='co'># We don't see systematic deviations, but heteroscedastic residuals</span>
</div><div class='img'><img src='loftest-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># therefore we should consider adapting the error model, although we have</span>
<span class='fu'>loftest</span><span class='op'>(</span><span class='va'>dfop_fit</span><span class='op'>)</span> <span class='co'># no lack of fit</span>
</div><div class='output co'>#> Likelihood ratio test
#>
#> Model 1: ANOVA with error model const
#> Model 2: DFOP with error model const
#> #Df LogLik Df Chisq Pr(>Chisq)
#> 1 10 -40.710
#> 2 5 -42.453 -5 3.485 0.6257</div><div class='input'><span class='co'>#</span>
<span class='co'># This is the anova model used internally for the comparison</span>
<span class='va'>test_data_anova</span> <span class='op'><-</span> <span class='va'>test_data</span>
<span class='va'>test_data_anova</span><span class='op'>$</span><span class='va'>time</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span><span class='op'>(</span><span class='va'>test_data_anova</span><span class='op'>$</span><span class='va'>time</span><span class='op'>)</span>
<span class='va'>anova_fit</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span><span class='op'>(</span><span class='va'>value</span> <span class='op'>~</span> <span class='va'>time</span>, data <span class='op'>=</span> <span class='va'>test_data_anova</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>anova_fit</span><span class='op'>)</span>
</div><div class='output co'>#>
#> Call:
#> lm(formula = value ~ time, data = test_data_anova)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -6.1000 -0.5625 0.0000 0.5625 6.1000
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 103.150 2.323 44.409 7.44e-12 ***
#> time1 -19.950 3.285 -6.073 0.000185 ***
#> time3 -50.800 3.285 -15.465 8.65e-08 ***
#> time7 -68.500 3.285 -20.854 6.28e-09 ***
#> time14 -79.750 3.285 -24.278 1.63e-09 ***
#> time28 -86.000 3.285 -26.181 8.35e-10 ***
#> time60 -94.900 3.285 -28.891 3.48e-10 ***
#> time90 -98.500 3.285 -29.986 2.49e-10 ***
#> time120 -100.450 3.285 -30.580 2.09e-10 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 3.285 on 9 degrees of freedom
#> Multiple R-squared: 0.9953, Adjusted R-squared: 0.9912
#> F-statistic: 240.5 on 8 and 9 DF, p-value: 1.417e-09
#> </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/logLik.html'>logLik</a></span><span class='op'>(</span><span class='va'>anova_fit</span><span class='op'>)</span> <span class='co'># We get the same likelihood and degrees of freedom</span>
</div><div class='output co'>#> 'log Lik.' -40.71015 (df=10)</div><div class='input'><span class='co'>#</span>
<span class='va'>test_data_2</span> <span class='op'><-</span> <span class='va'>synthetic_data_for_UBA_2014</span><span class='op'>[[</span><span class='fl'>12</span><span class='op'>]</span><span class='op'>]</span><span class='op'>$</span><span class='va'>data</span>
<span class='va'>m_synth_SFO_lin</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"M1"</span><span class='op'>)</span>,
M1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"M2"</span><span class='op'>)</span>,
M2 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span>
</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>sfo_lin_fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>m_synth_SFO_lin</span>, <span class='va'>test_data_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span><span class='op'>(</span><span class='va'>sfo_lin_fit</span><span class='op'>)</span> <span class='co'># not a good model, we try parallel formation</span>
</div><div class='img'><img src='loftest-3.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>loftest</span><span class='op'>(</span><span class='va'>sfo_lin_fit</span><span class='op'>)</span>
</div><div class='output co'>#> Likelihood ratio test
#>
#> Model 1: ANOVA with error model const
#> Model 2: m_synth_SFO_lin with error model const and fixed parameter(s) M1_0, M2_0
#> #Df LogLik Df Chisq Pr(>Chisq)
#> 1 28 -93.606
#> 2 7 -171.927 -21 156.64 < 2.2e-16 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'>#</span>
<span class='va'>m_synth_SFO_par</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <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'>"M1"</span>, <span class='st'>"M2"</span><span class='op'>)</span><span class='op'>)</span>,
M1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>,
M2 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span>
</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>sfo_par_fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>m_synth_SFO_par</span>, <span class='va'>test_data_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span><span class='op'>(</span><span class='va'>sfo_par_fit</span><span class='op'>)</span> <span class='co'># much better for metabolites</span>
</div><div class='img'><img src='loftest-4.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>loftest</span><span class='op'>(</span><span class='va'>sfo_par_fit</span><span class='op'>)</span>
</div><div class='output co'>#> Likelihood ratio test
#>
#> Model 1: ANOVA with error model const
#> Model 2: m_synth_SFO_par with error model const and fixed parameter(s) M1_0, M2_0
#> #Df LogLik Df Chisq Pr(>Chisq)
#> 1 28 -93.606
#> 2 7 -156.331 -21 125.45 < 2.2e-16 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'>#</span>
<span class='va'>m_synth_DFOP_par</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"DFOP"</span>, to <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'>"M1"</span>, <span class='st'>"M2"</span><span class='op'>)</span><span class='op'>)</span>,
M1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>,
M2 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span>
</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>dfop_par_fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>m_synth_DFOP_par</span>, <span class='va'>test_data_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span><span class='op'>(</span><span class='va'>dfop_par_fit</span><span class='op'>)</span> <span class='co'># No visual lack of fit</span>
</div><div class='img'><img src='loftest-5.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>loftest</span><span class='op'>(</span><span class='va'>dfop_par_fit</span><span class='op'>)</span> <span class='co'># no lack of fit found by the test</span>
</div><div class='output co'>#> Likelihood ratio test
#>
#> Model 1: ANOVA with error model const
#> Model 2: m_synth_DFOP_par with error model const and fixed parameter(s) M1_0, M2_0
#> #Df LogLik Df Chisq Pr(>Chisq)
#> 1 28 -93.606
#> 2 9 -102.763 -19 18.313 0.5016</div><div class='input'><span class='co'>#</span>
<span class='co'># The anova model used for comparison in the case of transformation products</span>
<span class='va'>test_data_anova_2</span> <span class='op'><-</span> <span class='va'>dfop_par_fit</span><span class='op'>$</span><span class='va'>data</span>
<span class='va'>test_data_anova_2</span><span class='op'>$</span><span class='va'>variable</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span><span class='op'>(</span><span class='va'>test_data_anova_2</span><span class='op'>$</span><span class='va'>variable</span><span class='op'>)</span>
<span class='va'>test_data_anova_2</span><span class='op'>$</span><span class='va'>time</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span><span class='op'>(</span><span class='va'>test_data_anova_2</span><span class='op'>$</span><span class='va'>time</span><span class='op'>)</span>
<span class='va'>anova_fit_2</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span><span class='op'>(</span><span class='va'>observed</span> <span class='op'>~</span> <span class='va'>time</span><span class='op'>:</span><span class='va'>variable</span> <span class='op'>-</span> <span class='fl'>1</span>, data <span class='op'>=</span> <span class='va'>test_data_anova_2</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>anova_fit_2</span><span class='op'>)</span>
</div><div class='output co'>#>
#> Call:
#> lm(formula = observed ~ time:variable - 1, data = test_data_anova_2)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -6.1000 -0.5875 0.0000 0.5875 6.1000
#>
#> Coefficients: (2 not defined because of singularities)
#> Estimate Std. Error t value Pr(>|t|)
#> time0:variableparent 103.150 1.573 65.562 < 2e-16 ***
#> time1:variableparent 83.200 1.573 52.882 < 2e-16 ***
#> time3:variableparent 52.350 1.573 33.274 < 2e-16 ***
#> time7:variableparent 34.650 1.573 22.024 < 2e-16 ***
#> time14:variableparent 23.400 1.573 14.873 6.35e-14 ***
#> time28:variableparent 17.150 1.573 10.901 5.47e-11 ***
#> time60:variableparent 8.250 1.573 5.244 1.99e-05 ***
#> time90:variableparent 4.650 1.573 2.956 0.006717 **
#> time120:variableparent 2.700 1.573 1.716 0.098507 .
#> time0:variableM1 NA NA NA NA
#> time1:variableM1 11.850 1.573 7.532 6.93e-08 ***
#> time3:variableM1 22.700 1.573 14.428 1.26e-13 ***
#> time7:variableM1 33.050 1.573 21.007 < 2e-16 ***
#> time14:variableM1 31.250 1.573 19.863 < 2e-16 ***
#> time28:variableM1 18.900 1.573 12.013 7.02e-12 ***
#> time60:variableM1 7.550 1.573 4.799 6.28e-05 ***
#> time90:variableM1 3.850 1.573 2.447 0.021772 *
#> time120:variableM1 2.050 1.573 1.303 0.204454
#> time0:variableM2 NA NA NA NA
#> time1:variableM2 6.700 1.573 4.259 0.000254 ***
#> time3:variableM2 16.750 1.573 10.646 8.93e-11 ***
#> time7:variableM2 25.800 1.573 16.399 6.89e-15 ***
#> time14:variableM2 28.600 1.573 18.178 6.35e-16 ***
#> time28:variableM2 25.400 1.573 16.144 9.85e-15 ***
#> time60:variableM2 21.600 1.573 13.729 3.81e-13 ***
#> time90:variableM2 17.800 1.573 11.314 2.51e-11 ***
#> time120:variableM2 14.100 1.573 8.962 2.79e-09 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 2.225 on 25 degrees of freedom
#> Multiple R-squared: 0.9979, Adjusted R-squared: 0.9957
#> F-statistic: 469.2 on 25 and 25 DF, p-value: < 2.2e-16
#> </div><div class='input'><span class='co'># }</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 Johannes Ranke.</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>
|
