title: specific manipulation of axis limits and scales in sjplot::plot_model of logistic glmer that generally preserves plot_model output
body: <p>Sorry if this is a double post, I've seen some similar posts but haven't found the exact solution I'm looking for.</p>
  <p>I fit a glmer model to some reaction time data of the form:</p>
  <pre><code>m19 &lt;- glmer(response ~ trial_z*stim + cond  + (1 + stim | subj_idx), 
               na.action = na.exclude,  
               data = gng, family = &quot;binomial&quot;, 
               control = glmerControl(optCtrl = list(maxfun = 50000)))
  </code></pre>
  <p>where: <code>response</code> is binary (correct response, incorrect response) on a standard go/no-go task.</p>
  <p>I want to plot odds ratios of the fixed effects using the <code>sjplot::plot_model</code> function but don't seem to be able to get things looking quite right.</p>
  <p>I want to plot these odds ratios for the fixed effects in my model:</p>
  <pre><code>library(broom.mixed)
  tidy(m19,conf.int=TRUE,exponentiate=TRUE,effects=&quot;fixed&quot;)
  </code></pre>
  <p>which looks like:</p>
  <pre><code># A tibble: 7 x 8
    effect term              estimate std.error statistic  p.value  conf.low conf.high
    &lt;chr&gt;  &lt;chr&gt;                &lt;dbl&gt;     &lt;dbl&gt;     &lt;dbl&gt;    &lt;dbl&gt;     &lt;dbl&gt;     &lt;dbl&gt;
  1 fixed  (Intercept)      414.      123.          20.2  6.98e-91 231.       742.    
  2 fixed  trial_z            0.697     0.0751      -3.35 7.97e- 4   0.564      0.860 
  3 fixed  stimNoGo           0.00925   0.00257    -16.9  6.80e-64   0.00537    0.0159
  4 fixed  condThreeGo        1.48      0.151        3.82 1.32e- 4   1.21       1.80  
  5 fixed  condFiveGo         1.69      0.174        5.07 4.08e- 7   1.38       2.06  
  6 fixed  condSevenGo        1.51      0.151        4.07 4.73e- 5   1.24       1.83  
  7 fixed  trial_z:stimNoGo   1.30      0.149        2.28 2.25e- 2   1.04       1.63  
  </code></pre>
  <p>The following sjplot call produces the following plot object:</p>
  <pre><code>gg &lt;- plot_model(m19, type=&quot;std&quot;, show.p=TRUE, ci.lvl=.95, dot.size=5, 
                   line.size=2, vline.color = &quot;black&quot;, axis.lim=c(.001, 2.25)) + 
    theme_bw(base_size=24) +
    theme(panel.grid.major.y=element_blank()) +
    ggtitle(&quot;&quot;) + 
    ylab(&quot;Odds Ratio&quot;)
  plot(gg)
  </code></pre>
  <p><a href="https://i.stack.imgur.com/Ec2ml.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Ec2ml.png" alt="attempt 1" /></a></p>
  <p>So I tried editing axis.limits within the call:</p>
  <pre><code>gg2 &lt;- plot_model(m19, type=&quot;std&quot;, show.p=TRUE, ci.lvl=.95, dot.size=5, 
                    line.size=2, vline.color = &quot;black&quot;, axis.lim=c(.001, 11)) + 
    theme_bw(base_size=24) +
    theme(panel.grid.major.y=element_blank()) +
    ggtitle(&quot;&quot;) + 
    ylab(&quot;Odds Ratio&quot;)
  
  plot(gg2)
  </code></pre>
  <p>Somewhat annoyingly, bumping the second concatenated axis.lim element to anything between 1 and 10 produced my attempt 1, but then anything above 10 sets that limit in the plot to 100 (not sure why this is...)</p>
  <p><a href="https://i.stack.imgur.com/927R1.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/927R1.png" alt="attempt 2" /></a></p>
  <p>So I tried, based off other posts to edit the axes post-hoc:</p>
  <pre><code>gg + ylim(.001, 2.25)
  </code></pre>
  <p><a href="https://i.stack.imgur.com/iphwY.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/iphwY.png" alt="attempt 3" /></a></p>
  <p>My question:</p>
  <p>I'd like a plot that is somewhat of a combination of attempt 2 and attempt 3.</p>
  <p>In 2 I like that the scaling below and above 1 are different and that 1 (equal odds) has a special denotion that demonstrates that CIs that overlap with 1 represent a null effect. If I want than within <code>plot_model()</code>'s capabilities I am stuck at how I can get the axis to the right of that 1 mark to look more like the scale in attempt 3, which wipes out the nice delineation of odds for and against and sets the scale as uniform across all y values (also, this was certainly confusing at first, given that I'm looking to manage what the user sees on the x-axis. I assume there's a <code>coord_flip</code> call somewhere in the function...).</p>
  <p>If I can clarify further lmk. Thanks for your input!</p>