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| diff --git a/docs/reference/index.html b/docs/reference/index.html index 1c9975e0..0947ff94 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -215,6 +215,12 @@ more datasets</p></td>        </tr><tr>          <td> +          <p><code><a href="loftest.html">loftest()</a></code> </p> +        </td> +        <td><p>Lack-of-fit test for models fitted to data with replicates</p></td> +      </tr><tr> +         +        <td>            <p><code><a href="mkinerrmin.html">mkinerrmin()</a></code> </p>          </td>          <td><p>Calculate the minimum error to assume in order to pass the variance test</p></td> diff --git a/docs/reference/loftest-1.png b/docs/reference/loftest-1.pngBinary files differ new file mode 100644 index 00000000..3d20f41e --- /dev/null +++ b/docs/reference/loftest-1.png diff --git a/docs/reference/loftest-2.png b/docs/reference/loftest-2.pngBinary files differ new file mode 100644 index 00000000..be8bf815 --- /dev/null +++ b/docs/reference/loftest-2.png diff --git a/docs/reference/loftest-3.png b/docs/reference/loftest-3.pngBinary files differ new file mode 100644 index 00000000..c66c95f1 --- /dev/null +++ b/docs/reference/loftest-3.png diff --git a/docs/reference/loftest-4.png b/docs/reference/loftest-4.pngBinary files differ new file mode 100644 index 00000000..da86d97f --- /dev/null +++ b/docs/reference/loftest-4.png diff --git a/docs/reference/loftest-5.png b/docs/reference/loftest-5.pngBinary files differ new file mode 100644 index 00000000..54b176e7 --- /dev/null +++ b/docs/reference/loftest-5.png diff --git a/docs/reference/loftest.html b/docs/reference/loftest.html new file mode 100644 index 00000000..757f0bbe --- /dev/null +++ b/docs/reference/loftest.html @@ -0,0 +1,343 @@ +<!-- 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/3.3.1/jquery.min.js" integrity="sha256-FgpCb/KJQlLNfOu91ta32o/NMZxltwRo8QtmkMRdAu8=" crossorigin="anonymous"></script> +<!-- Bootstrap --> + +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/css/bootstrap.min.css" integrity="sha256-916EbMg70RQy9LHiGkXzG8hSg9EdNy97GazNG/aiY1w=" crossorigin="anonymous" /> + +<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha256-U5ZEeKfGNOja007MMD3YBI0A3OSZOQbeG6z2f2Y0hu8=" crossorigin="anonymous"></script> + +<!-- Font Awesome icons --> +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.7.1/css/all.min.css" integrity="sha256-nAmazAk6vS34Xqo0BSrTb+abbtFlgsFK7NKSi6o7Y78=" crossorigin="anonymous" /> +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.7.1/css/v4-shims.min.css" integrity="sha256-6qHlizsOWFskGlwVOKuns+D1nB6ssZrHQrNj1wGplHc=" crossorigin="anonymous" /> + +<!-- clipboard.js --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.4/clipboard.min.js" integrity="sha256-FiZwavyI2V6+EXO1U+xzLG3IKldpiTFf3153ea9zikQ=" crossorigin="anonymous"></script> + +<!-- headroom.js --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.9.4/headroom.min.js" integrity="sha256-DJFC1kqIhelURkuza0AvYal5RxMtpzLjFhsnVIeuk+U=" crossorigin="anonymous"></script> +<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.9.4/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. 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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='no'>object</span>, <span class='no'>...</span>) + +<span class='co'># S3 method for mkinfit</span> +<span class='fu'>loftest</span>(<span class='no'>object</span>, <span class='no'>...</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='no'>test_data</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span>(<span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>12</span>]]$<span class='no'>data</span>, <span class='no'>name</span> <span class='kw'>==</span> <span class='st'>"parent"</span>) +<span class='no'>sfo_fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='st'>"SFO"</span>, <span class='no'>test_data</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span>(<span class='no'>sfo_fit</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='no'>sfo_fit</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='no'>dfop_fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='st'>"DFOP"</span>, <span class='no'>test_data</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span>(<span class='no'>dfop_fit</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='no'>dfop_fit</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='no'>test_data_anova</span> <span class='kw'><-</span> <span class='no'>test_data</span> +<span class='no'>test_data_anova</span>$<span class='no'>time</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span>(<span class='no'>test_data_anova</span>$<span class='no'>time</span>) +<span class='no'>anova_fit</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span>(<span class='no'>value</span> ~ <span class='no'>time</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>test_data_anova</span>) +<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>anova_fit</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='no'>anova_fit</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='no'>test_data_2</span> <span class='kw'><-</span> <span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>12</span>]]$<span class='no'>data</span> +<span class='no'>m_synth_SFO_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>), +  <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>), +  <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='no'>sfo_lin_fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_SFO_lin</span>, <span class='no'>test_data_2</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span>(<span class='no'>sfo_lin_fit</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='no'>sfo_lin_fit</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='no'>m_synth_SFO_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>)), +  <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), +  <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='no'>sfo_par_fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_SFO_par</span>, <span class='no'>test_data_2</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span>(<span class='no'>sfo_par_fit</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='no'>sfo_par_fit</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='no'>m_synth_DFOP_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"DFOP"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>)), +  <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), +  <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='no'>dfop_par_fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_DFOP_par</span>, <span class='no'>test_data_2</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_res</a></span>(<span class='no'>dfop_par_fit</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='no'>dfop_par_fit</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='no'>test_data_anova_2</span> <span class='kw'><-</span> <span class='no'>dfop_par_fit</span>$<span class='no'>data</span> +<span class='no'>test_data_anova_2</span>$<span class='no'>variable</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span>(<span class='no'>test_data_anova_2</span>$<span class='no'>variable</span>) +<span class='no'>test_data_anova_2</span>$<span class='no'>time</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/factor.html'>as.factor</a></span>(<span class='no'>test_data_anova_2</span>$<span class='no'>time</span>) +<span class='no'>anova_fit_2</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span>(<span class='no'>observed</span> ~ <span class='no'>time</span>:<span class='no'>variable</span> - <span class='fl'>1</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>test_data_anova_2</span>) +<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>anova_fit_2</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'># } +</div></pre> +  </div> +  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> +    <h2>Contents</h2> +    <ul class="nav nav-pills nav-stacked"> +      <li><a href="#arguments">Arguments</a></li> +      <li><a href="#details">Details</a></li> +      <li><a href="#see-also">See also</a></li> +      <li><a href="#examples">Examples</a></li> +    </ul> + +  </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> 1.4.1.</p> +</div> + +      </footer> +   </div> + +   + + +  </body> +</html> + + | 
