title: Omit the constant and shift values into the correct location in stargazer in R
body: <p>I want to input the average marginal effects into a <code>stargazer</code> table in R.</p>
  <p>The problem is that stargazer is treating the first marginal effects value as the constant in the table. The average marginal effects that I'm calculating do not include a constant. Therefore, I want to omit it from the table. Using the <code>omit</code> argument in stargazer just excludes the term altogether. Because it treats the first marginal effects value as the constant, it actually drops a coefficient.</p>
  <p>How can I get stargazer to omit the constant while getting it to recognize the first value is actually a coefficient, not the constant?</p>
  <p>Here is an example of the problem:</p>
  <pre><code>#devtools::install_github(&quot;vincentarelbundock/marginaleffects&quot;)
  library(marginaleffects)
  library(stargazer)
  
  Y &lt;- sample(c(0,1), 1000, replace = T)
  X &lt;- sample(seq(1,50,1), 1000, replace = T)
  Z &lt;- sample(seq(1,50,1), 1000, replace = T)
  
  DF &lt;- data.frame(Y,X, Z)
  Test &lt;- glm(Y ~ X + Z, data = DF, family=binomial())
  Test_DF &lt;- data.frame(summary(marginaleffects(Test)))
  
  Test_DF
  
  #********************* Table **********************
  #Fake Regression - to Make Table
  Fake_RE &lt;- glm(Y ~ X + Z, data = DF, family=binomial())
  
  stargazer(list(Fake_RE), type = &quot;text&quot;,
            coef = list(Test_DF$estimate),
            se = list(Test_DF$std.error))
  
  </code></pre>
  <p>Average Marginal Effects:</p>
  <pre><code>&gt; Test_DF
        type term     estimate   std.error statistic   p.value     conf.low    conf.high
  1 response    X  0.001540192 0.001109148  1.388627 0.1649462 -0.000633697 0.0037140816
  2 response    Z -0.001215714 0.001087828 -1.117561 0.2637546 -0.003347817 0.000916389
  
  </code></pre>
  <p>Subsequent Table:</p>
  <pre><code>&gt; stargazer(list(Fake_RE), type = &quot;text&quot;,
  +           coef = list(Test_DF$estimate),
  +           se = list(Test_DF$std.error))
  
  =============================================
                        Dependent variable:    
                    ---------------------------
                                 Y             
  ---------------------------------------------
  X                           -0.001           
                              (0.001)          
                                               
  Z                                            
                                               
                                               
  Constant                     0.002           
                              (0.001)          
                                               
  ---------------------------------------------
  Observations                 1,000           
  Log Likelihood             -690.097          
  Akaike Inf. Crit.          1,386.194         
  =============================================
  Note:             *p&lt;0.1; **p&lt;0.05; ***p&lt;0.01
  
  </code></pre>