diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2022-01-11 19:57:58 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2022-01-11 19:57:58 +0100 |
| commit | c0638c84568d475b3b059e2c6e593e6f03b846bc (patch) | |
| tree | f98c56eca28c836280364c1d85577686395d1096 /docs/dev/articles/web_only | |
| parent | e7751e791f46b2aa334f52109e0bd8211dfd7083 (diff) | |
Update static docsnlmixr
Diffstat (limited to 'docs/dev/articles/web_only')
13 files changed, 137 insertions, 149 deletions
diff --git a/docs/dev/articles/web_only/dimethenamid_2018.html b/docs/dev/articles/web_only/dimethenamid_2018.html index 13b0f98e..a2ea5c8d 100644 --- a/docs/dev/articles/web_only/dimethenamid_2018.html +++ b/docs/dev/articles/web_only/dimethenamid_2018.html @@ -101,7 +101,7 @@ <h1 data-toc-skip>Example evaluations of the dimethenamid data from 2018</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">Last change 27 September 2021, built on 05 Okt 2021</h4> + <h4 class="date">Last change 11 January 2022, built on 11 Jan 2022</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/master/vignettes/web_only/dimethenamid_2018.rmd"><code>vignettes/web_only/dimethenamid_2018.rmd</code></a></small> <div class="hidden name"><code>dimethenamid_2018.rmd</code></div> @@ -151,20 +151,20 @@ error_model <span class="op">=</span> <span class="st">"tc"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> <p>The plot of the individual SFO fits shown below suggests that at least in some datasets the degradation slows down towards later time points, and that the scatter of the residuals error is smaller for smaller values (panel to the right):</p> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_sfo_const-1.png" width="700"></p> <p>Using biexponential decline (DFOP) results in a slightly more random scatter of the residuals:</p> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const-1.png" width="700"></p> <p>The population curve (bold line) in the above plot results from taking the mean of the individual transformed parameters, i.e. of log k1 and log k2, as well as of the logit of the g parameter of the DFOP model). Here, this procedure does not result in parameters that represent the degradation well, because in some datasets the fitted value for k2 is extremely close to zero, leading to a log k2 value that dominates the average. This is alleviated if only rate constants that pass the t-test for significant difference from zero (on the untransformed scale) are considered in the averaging:</p> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const_test-1.png" width="700"></p> <p>While this is visually much more satisfactory, such an average procedure could introduce a bias, as not all results from the individual fits enter the population curve with the same weight. This is where nonlinear mixed-effects models can help out by treating all datasets with equally by fitting a parameter distribution model together with the degradation model and the error model (see below).</p> <p>The remaining trend of the residuals to be higher for higher predicted residues is reduced by using the two-component error model:</p> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_tc_test-1.png" width="700"></p> </div> <div id="nonlinear-mixed-effects-models" class="section level2"> @@ -205,7 +205,7 @@ f_parent_nlme_dfop_tc 3 10 671.91 702.34 -325.96 2 vs 3 134.69 <.0001 <p>While the SFO variants converge fast, the additional parameters introduced by this lead to convergence warnings for the DFOP model. The model comparison clearly show that adding correlations between random effects does not improve the fits.</p> <p>The selected model (DFOP with two-component error) fitted to the data assuming no correlations between random effects is shown below.</p> <div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/plot_parent_nlme-1.png" width="700"></p> </div> <div id="saemix" class="section level3"> @@ -217,50 +217,54 @@ f_parent_nlme_dfop_tc 3 10 671.91 702.34 -325.96 2 vs 3 134.69 <.0001 <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span> <span class="va">saemix_control</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html">saemixControl</a></span><span class="op">(</span>nbiter.saemix <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="fl">800</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> -<span class="va">saemix_control_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html">saemixControl</a></span><span class="op">(</span>nbiter.saemix <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="fl">10000</span>, <span class="fl">1000</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, +<span class="va">saemix_control_moreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html">saemixControl</a></span><span class="op">(</span>nbiter.saemix <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="fl">1600</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> <p>The convergence plot for the SFO model using constant variance is shown below.</p> <div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_sfo_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_sfo_const-1.png" width="700"></p> <p>Obviously the default number of iterations is sufficient to reach convergence. This can also be said for the SFO fit using the two-component error model.</p> <div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_sfo_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_sfo_tc-1.png" width="700"></p> <p>When fitting the DFOP model with constant variance (see below), parameter convergence is not as unambiguous.</p> <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_dfop_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_const-1.png" width="700"></p> <p>This is improved when the DFOP model is fitted with the two-component error model. Convergence of the variance of k2 is enhanced, it remains more or less stable already after 200 iterations of the first phase.</p> <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc-1.png" width="700"></p> -<p>We also check if using many more iterations (10 000 for the first and 1000 for the second phase) improve the result in a significant way. The AIC values obtained are compared further below.</p> <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc_10k</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control_10k</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_10k</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc_10k-1.png" width="700"></p> +<code class="sourceCode R"><span class="co"># The last time I tried (2022-01-11) this gives an error in solve.default(omega.eta)</span> +<span class="co"># system is computationally singular: reciprocal condition number = 5e-17</span> +<span class="co">#f_parent_saemix_dfop_tc_10k <- mkin::saem(f_parent_mkin_tc["DFOP", ], quiet = TRUE,</span> +<span class="co"># control = saemix_control_10k, transformations = "saemix")</span> +<span class="co"># Now we do not get a significant improvement by using twice the number of iterations</span> +<span class="va">f_parent_saemix_dfop_tc_moreiter</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, + control <span class="op">=</span> <span class="va">saemix_control_moreiter</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> +<span class="co">#plot(f_parent_saemix_dfop_tc_moreiter$so, plot.type = "convergence")</span></code></pre></div> <p>An alternative way to fit DFOP in combination with the two-component error model is to use the model formulation with transformed parameters as used per default in mkin.</p> <div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc_mkin</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc_mkin-1.png" width="700"></p> -<p>As the convergence plots do not clearly indicate that the algorithm has converged, we again use a much larger number of iterations, which leads to satisfactory convergence (see below).</p> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc_mkin-1.png" width="700"> As the convergence plots do not clearly indicate that the algorithm has converged, we again use four times the number of iterations, which leads to almost satisfactory convergence (see below).</p> <div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc_mkin_10k</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control_10k</span>, transformations <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin_10k</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc_mkin_10k-1.png" width="700"></p> +<code class="sourceCode R"><span class="va">saemix_control_muchmoreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">3200</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, + print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> +<span class="va">f_parent_saemix_dfop_tc_mkin_muchmoreiter</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, + control <span class="op">=</span> <span class="va">saemix_control_muchmoreiter</span>, transformations <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span> +<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin_muchmoreiter</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc_mkin_moreiter-1.png" width="700"></p> <p>The four combinations (SFO/const, SFO/tc, DFOP/const and DFOP/tc), including the variations of the DFOP/tc combination can be compared using the model comparison function of the saemix package:</p> <div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">AIC_parent_saemix</span> <span class="op"><-</span> <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html">compare.saemix</a></span><span class="op">(</span> @@ -268,9 +272,9 @@ f_parent_nlme_dfop_tc 3 10 671.91 702.34 -325.96 2 vs 3 134.69 <.0001 <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_tc_10k</span><span class="op">$</span><span class="va">so</span>, + <span class="va">f_parent_saemix_dfop_tc_moreiter</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_tc_mkin</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_tc_mkin_10k</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></code></pre></div> + <span class="va">f_parent_saemix_dfop_tc_mkin_muchmoreiter</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></code></pre></div> <pre><code>Likelihoods calculated by importance sampling</code></pre> <div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/colnames.html">rownames</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span> @@ -278,14 +282,14 @@ f_parent_nlme_dfop_tc 3 10 671.91 702.34 -325.96 2 vs 3 134.69 <.0001 <span class="st">"DFOP tc mkintrans"</span>, <span class="st">"DFOP tc mkintrans more iterations"</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span></code></pre></div> <pre><code> AIC BIC -SFO const 796.37 795.33 -SFO tc 798.37 797.13 -DFOP const 713.16 711.28 -DFOP tc 666.10 664.01 -DFOP tc more iterations 666.15 664.06 -DFOP tc mkintrans 682.26 680.17 -DFOP tc mkintrans more iterations 666.12 664.04</code></pre> -<p>As in the case of nlme fits, the DFOP model fitted with two-component error (number 4) gives the lowest AIC. Using a much larger number of iterations does not improve the fit a lot. When the mkin transformations are used instead of the saemix transformations, this large number of iterations leads to a goodness of fit that is comparable to the result obtained with saemix transformations.</p> +SFO const 796.38 795.34 +SFO tc 798.38 797.13 +DFOP const 705.75 703.88 +DFOP tc 665.65 663.57 +DFOP tc more iterations 665.88 663.80 +DFOP tc mkintrans 674.02 671.94 +DFOP tc mkintrans more iterations 667.94 665.86</code></pre> +<p>As in the case of nlme fits, the DFOP model fitted with two-component error (number 4) gives the lowest AIC. Using a much larger number of iterations does not significantly change the AIC. When the mkin transformations are used instead of the saemix transformations, we need four times the number of iterations to obtain a goodness of fit that almost as good as the result obtained with saemix transformations.</p> <p>In order to check the influence of the likelihood calculation algorithms implemented in saemix, the likelihood from Gaussian quadrature is added to the best fit, and the AIC values obtained from the three methods are compared.</p> <div class="sourceCode" id="cb24"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span> <span class="op"><-</span> @@ -297,7 +301,7 @@ DFOP tc mkintrans more iterations 666.12 664.04</code></pre> <span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix_methods</span><span class="op">)</span></code></pre></div> <pre><code> is gq lin -666.10 666.03 665.48 </code></pre> +665.65 665.68 665.11 </code></pre> <p>The AIC values based on importance sampling and Gaussian quadrature are very similar. Using linearisation is known to be less accurate, but still gives a similar value.</p> </div> <div id="nlmixr" class="section level3"> @@ -327,72 +331,78 @@ DFOP tc mkintrans more iterations 666.12 664.04</code></pre> <span class="st">"AIC (nlme)"</span> <span class="op">=</span> <span class="va">aic_nlme</span>, <span class="st">"AIC (nlmixr with FOCEI)"</span> <span class="op">=</span> <span class="va">aic_nlmixr_focei</span>, check.names <span class="op">=</span> <span class="cn">FALSE</span> -<span class="op">)</span></code></pre></div> +<span class="op">)</span> +<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">aic_nlme_nlmixr_focei</span><span class="op">)</span></code></pre></div> +<pre><code> Degradation model Error model AIC (nlme) AIC (nlmixr with FOCEI) +1 SFO constant variance 796.60 796.60 +2 SFO two-component NA 798.64 +3 DFOP constant variance 798.60 745.87 +4 DFOP two-component 671.91 740.42</code></pre> <p>Secondly, we use the SAEM estimation routine and check the convergence plots. The control parameters also used for the saemix fits are defined beforehand.</p> -<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">nlmixr_saem_control_800</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, nBurn <span class="op">=</span> <span class="fl">800</span>, nEm <span class="op">=</span> <span class="fl">300</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span> <span class="va">nlmixr_saem_control_1000</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, nBurn <span class="op">=</span> <span class="fl">1000</span>, nEm <span class="op">=</span> <span class="fl">300</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span> <span class="va">nlmixr_saem_control_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, nBurn <span class="op">=</span> <span class="fl">10000</span>, nEm <span class="op">=</span> <span class="fl">1000</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span></code></pre></div> -<p>The we fit SFO with constant variance</p> -<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> +<p>Then we fit SFO with constant variance</p> +<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_sfo_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_const</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_sfo_const-1.png" width="700"></p> <p>and SFO with two-component error.</p> -<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_sfo_tc-1.png" width="700"></p> -<p>For DFOP with constant variance, the convergence plots show considerable instability of the fit, which indicates overparameterisation which was already observed earlier for this model combination.</p> -<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> +<p>For DFOP with constant variance, the convergence plots show considerable instability of the fit, which indicates overparameterisation which was already observed above for this model combination.</p> +<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_const</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_const-1.png" width="700"></p> <p>For DFOP with two-component error, a less erratic convergence is seen.</p> -<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc-1.png" width="700"></p> <p>To check if an increase in the number of iterations improves the fit, we repeat the fit with 1000 iterations for the burn in phase and 300 iterations for the second phase.</p> -<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc_1000</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_1000</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc_1000</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc_1k-1.png" width="700"></p> <p>Here the fit looks very similar, but we will see below that it shows a higher AIC than the fit with 800 iterations in the burn in phase. Next we choose 10 000 iterations for the burn in phase and 1000 iterations for the second phase for comparison with saemix.</p> -<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, control <span class="op">=</span> <span class="va">nlmixr_saem_control_10k</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc_10k-1.png" width="700"></p> <p>In the above convergence plot, the time course of ‘eta.DMTA_0’ and ‘log_k2’ indicate a false convergence.</p> <p>The AIC values are internally calculated using Gaussian quadrature.</p> -<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/AIC.html">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_sfo_tc</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_tc_1000</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<pre><code> df AIC -f_parent_nlmixr_saem_sfo_const$nm 5 798.69 -f_parent_nlmixr_saem_sfo_tc$nm 6 810.33 -f_parent_nlmixr_saem_dfop_const$nm 9 736.00 -f_parent_nlmixr_saem_dfop_tc$nm 10 664.85 -f_parent_nlmixr_saem_dfop_tc_1000$nm 10 669.57 -f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> +<pre><code> df AIC +f_parent_nlmixr_saem_sfo_const$nm 5 798.71 +f_parent_nlmixr_saem_sfo_tc$nm 6 808.64 +f_parent_nlmixr_saem_dfop_const$nm 9 1995.96 +f_parent_nlmixr_saem_dfop_tc$nm 10 664.96 +f_parent_nlmixr_saem_dfop_tc_1000$nm 10 667.39 +f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> <p>We can see that again, the DFOP/tc model shows the best goodness of fit. However, increasing the number of burn-in iterations from 800 to 1000 results in a higher AIC. If we further increase the number of iterations to 10 000 (burn-in) and 1000 (second phase), the AIC cannot be calculated for the nlmixr/saem fit, supporting that the fit did not converge properly.</p> </div> <div id="comparison" class="section level3"> <h3 class="hasAnchor"> <a href="#comparison" class="anchor"></a>Comparison</h3> <p>The following table gives the AIC values obtained with the three packages using the same control parameters (800 iterations burn-in, 300 iterations second phase, 15 chains).</p> -<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="va">AIC_all</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span> check.names <span class="op">=</span> <span class="cn">FALSE</span>, <span class="st">"Degradation model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"SFO"</span>, <span class="st">"DFOP"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, @@ -420,168 +430,146 @@ f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> <td align="left">SFO</td> <td align="left">const</td> <td align="right">796.60</td> -<td align="right">796.62</td> -<td align="right">796.37</td> -<td align="right">798.69</td> +<td align="right">796.60</td> +<td align="right">796.38</td> +<td align="right">798.71</td> </tr> <tr class="even"> <td align="left">SFO</td> <td align="left">tc</td> <td align="right">798.60</td> -<td align="right">798.61</td> -<td align="right">798.37</td> -<td align="right">810.33</td> +<td align="right">798.64</td> +<td align="right">798.38</td> +<td align="right">808.64</td> </tr> <tr class="odd"> <td align="left">DFOP</td> <td align="left">const</td> <td align="right">NA</td> -<td align="right">750.91</td> -<td align="right">713.16</td> -<td align="right">736.00</td> +<td align="right">745.87</td> +<td align="right">705.75</td> +<td align="right">1995.96</td> </tr> <tr class="even"> <td align="left">DFOP</td> <td align="left">tc</td> <td align="right">671.91</td> -<td align="right">666.60</td> -<td align="right">666.10</td> -<td align="right">664.85</td> +<td align="right">740.42</td> +<td align="right">665.65</td> +<td align="right">664.96</td> </tr> </tbody> </table> -<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">)</span></code></pre></div> <pre><code>Approximate 95% confidence intervals Fixed effects: lower est. upper -DMTA_0 96.2802274 98.2761977 100.272168 -k1 0.0339753 0.0645487 0.095122 -k2 0.0058977 0.0088887 0.011880 -g 0.9064373 0.9514417 0.996446 +DMTA_0 96.3087887 98.2761715 100.243554 +k1 0.0336893 0.0643651 0.095041 +k2 0.0062993 0.0088001 0.011301 +g 0.9100426 0.9524920 0.994941 Random effects: - lower est. upper -sd(DMTA_0) 0.44404 2.102366 3.76069 -sd(k1) 0.25433 0.589731 0.92514 -sd(k2) -0.33139 0.099797 0.53099 -sd(g) 0.39606 1.092234 1.78841 + lower est. upper +sd(DMTA_0) 0.41868 2.0607469 3.70281 +sd(k1) 0.25611 0.5935653 0.93102 +sd(k2) -10.29603 0.0029188 10.30187 +sd(g) 0.38083 1.0572543 1.73368 - lower est. upper -a.1 0.863644 1.063021 1.262398 -b.1 0.022555 0.029599 0.036643</code></pre> -<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r"> + lower est. upper +a.1 0.86253 1.061610 1.260690 +b.1 0.02262 0.029666 0.036712</code></pre> +<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">)</span></code></pre></div> <pre><code>Approximate 95% confidence intervals Fixed effects: lower est. upper -DMTA_0 96.2802274 98.2761977 100.272168 -k1 0.0339753 0.0645487 0.095122 -k2 0.0058977 0.0088887 0.011880 -g 0.9064373 0.9514417 0.996446 - - Random effects: - lower est. upper -sd(DMTA_0) 0.44404 2.102366 3.76069 -sd(k1) 0.25433 0.589731 0.92514 -sd(k2) -0.33139 0.099797 0.53099 -sd(g) 0.39606 1.092234 1.78841 - - - lower est. upper -a.1 0.863644 1.063021 1.262398 -b.1 0.022555 0.029599 0.036643</code></pre> -<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_10k</span><span class="op">)</span></code></pre></div> -<pre><code>Approximate 95% confidence intervals - - Fixed effects: - lower est. upper -DMTA_0 96.3027896 98.2641150 100.225440 -k1 0.0338214 0.0644055 0.094990 -k2 0.0058857 0.0087896 0.011693 -g 0.9086138 0.9521421 0.995670 +DMTA_0 96.3087887 98.2761715 100.243554 +k1 0.0336893 0.0643651 0.095041 +k2 0.0062993 0.0088001 0.011301 +g 0.9100426 0.9524920 0.994941 Random effects: - lower est. upper -sd(DMTA_0) 0.41448 2.05327 3.69206 -sd(k1) 0.25507 0.59132 0.92758 -sd(k2) -0.36781 0.09016 0.54813 -sd(g) 0.38585 1.06994 1.75402 + lower est. upper +sd(DMTA_0) 0.41868 2.0607469 3.70281 +sd(k1) 0.25611 0.5935653 0.93102 +sd(k2) -10.29603 0.0029188 10.30187 +sd(g) 0.38083 1.0572543 1.73368 - lower est. upper -a.1 0.866273 1.066115 1.265957 -b.1 0.022501 0.029541 0.036581</code></pre> -<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin_10k</span><span class="op">)</span></code></pre></div> + lower est. upper +a.1 0.86253 1.061610 1.260690 +b.1 0.02262 0.029666 0.036712</code></pre> +<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_mkin_muchmoreiter</span><span class="op">)</span></code></pre></div> <pre><code>Approximate 95% confidence intervals Fixed effects: lower est. upper -DMTA_0 96.3021306 98.2736091 100.245088 -k1 0.0401701 0.0645140 0.103611 -k2 0.0064706 0.0089398 0.012351 -g 0.8817692 0.9511605 0.980716 +DMTA_0 96.3402070 98.2789378 100.217669 +k1 0.0397896 0.0641976 0.103578 +k2 0.0041987 0.0084427 0.016977 +g 0.8656257 0.9521509 0.983992 Random effects: - lower est. upper -sd(DMTA_0) 0.42392 2.068018 3.71212 -sd(log_k1) 0.25440 0.589877 0.92536 -sd(log_k2) -0.38431 0.084334 0.55298 -sd(g_qlogis) 0.39107 1.077303 1.76353 + lower est. upper +sd(DMTA_0) 0.38907 2.01821 3.64735 +sd(log_k1) 0.25653 0.59512 0.93371 +sd(log_k2) -0.20501 0.37610 0.95721 +sd(g_qlogis) 0.39712 1.18296 1.96879 lower est. upper -a.1 0.865291 1.064897 1.264504 -b.1 0.022491 0.029526 0.036561</code></pre> -<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r"> +a.1 0.868558 1.070260 1.271963 +b.1 0.022461 0.029505 0.036548</code></pre> +<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">)</span></code></pre></div> <pre><code>Approximate 95% confidence intervals Fixed effects: lower est. upper -DMTA_0 96.3059406 98.2990616 100.292183 -k1 0.0402306 0.0648255 0.104456 -k2 0.0067864 0.0093097 0.012771 -g 0.8769017 0.9505258 0.981067 +DMTA_0 96.3224806 98.2941093 100.265738 +k1 0.0402270 0.0648200 0.104448 +k2 0.0068547 0.0093928 0.012871 +g 0.8764066 0.9501419 0.980848 Random effects: lower est. upper -sd(DMTA_0) NA 1.724654 NA -sd(log_k1) NA 0.592808 NA -sd(log_k2) NA 0.010741 NA -sd(g_qlogis) NA 1.087349 NA +sd(DMTA_0) NA 1.686509 NA +sd(log_k1) NA 0.592805 NA +sd(log_k2) NA 0.009766 NA +sd(g_qlogis) NA 1.082616 NA lower est. upper -sigma_low NA 1.081809 NA -rsd_high NA 0.032051 NA</code></pre> -<div class="sourceCode" id="cb49"><pre class="downlit sourceCode r"> +sigma_low NA 1.081677 NA +rsd_high NA 0.032073 NA</code></pre> +<div class="sourceCode" id="cb48"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html">intervals</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span><span class="op">)</span></code></pre></div> <pre><code>Approximate 95% confidence intervals Fixed effects: - lower est. upper -DMTA_0 96.426510 97.8987836 99.371057 -k1 0.040006 0.0644407 0.103799 -k2 0.006748 0.0092476 0.012673 -g 0.879251 0.9511399 0.981147 + lower est. upper +DMTA_0 96.2302085 98.1641090 100.098010 +k1 0.0398514 0.0643909 0.104041 +k2 0.0066292 0.0090784 0.012432 +g 0.8831478 0.9527284 0.981734 Random effects: lower est. upper -sd(DMTA_0) NA 3.7049e-04 NA -sd(log_k1) NA 5.9221e-01 NA -sd(log_k2) NA 3.8628e-07 NA -sd(g_qlogis) NA 1.0694e+00 NA +sd(DMTA_0) NA 1.6257e+00 NA +sd(log_k1) NA 5.9627e-01 NA +sd(log_k2) NA 5.8400e-07 NA +sd(g_qlogis) NA 1.0676e+00 NA lower est. upper -sigma_low NA 1.082343 NA -rsd_high NA 0.034895 NA</code></pre> +sigma_low NA 1.087722 NA +rsd_high NA 0.031883 NA</code></pre> </div> </div> </div> diff --git a/docs/dev/articles/web_only/dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_const-1.png b/docs/dev/articles/web_only/dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_const-1.png Binary files 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