title: Formatted latex regression tables with multiple models from broom output?
body: <p>I have several models such as the example below for which I have estimates, standard errors, p-values, r2 etc. as data.frames in tidy format, but I don't have the original model objects (analysis was run on a different machine). </p>
  
  <pre><code>require(broom)
  model &lt;- lm(mpg ~ hp + cyl, mtcars)
  tidy_model &lt;- tidy(model)
  glance_model &lt;- glance(model)
  
  # tidy_model
  # # A tibble: 3 x 5
  #   term        estimate std.error statistic  p.value
  #   &lt;chr&gt;          &lt;dbl&gt;     &lt;dbl&gt;     &lt;dbl&gt;    &lt;dbl&gt;
  # 1 (Intercept)  36.9       2.19       16.8  1.62e-16
  # 2 hp           -0.0191    0.0150     -1.27 2.13e- 1
  # 3 cyl          -2.26      0.576      -3.93 4.80e- 4
  # glance(model)
  # # A tibble: 1 x 11
  #   r.squared adj.r.squared sigma ...
  # *     &lt;dbl&gt;         &lt;dbl&gt; &lt;dbl&gt;     ...
  # 1     0.760         0.743  3.06      ...
  </code></pre>
  
  <p>There exist several packages (e.g. <code>stargazer</code> or <code>texreg</code>) which transform one or more model objects (<code>lm</code>, <code>glm</code>, etc.) into well-formatted regression tables side-by-side, see below for an example of <code>texreg</code>:</p>
  
  <pre><code>require(texreg)
  screenreg(list(model1, model1)
  # =================================
  #              Model 1    Model 2  
  # ---------------------------------
  # (Intercept)  34.66 ***  34.66 ***
  #              (2.55)     (2.55)   
  # cyl          -1.59 *    -1.59 *  
  #              (0.71)     (0.71)   
  # disp         -0.02      -0.02    
  #              (0.01)     (0.01)   
  # ---------------------------------
  # R^2           0.76       0.76    
  # Adj. R^2      0.74       0.74    
  # Num. obs.    32         32       
  # RMSE          3.06       3.06    
  # =================================
  # *** p &lt; 0.001, ** p &lt; 0.01, * p &lt; 0.05
  </code></pre>
  
  <p>Is there a similar package that uses tidy estimation results produced with <code>broom</code> as inputs rather than model objects to produce a table such as the above example? </p>