title: How does sjPlot calculate significance?
body: <p>I would like to find out how sjPlot calculates significance so I can determine why some moderate correlations are insignificant in one table and low correlations are significant in another table.</p>
  
  <p>I am using the sjt.corr() function from sjPlot to create some correlations, and in this function I use the option "fade.ns=TRUE" so that insignificant correlations are faded out. However, I can't seem to find any documentation about how significance is calculated and I'm wondering how this works since it appears to be relative to all the other values in that particular table.</p>
  
  <p>I have included a reproducible example below. In the 'USArrests' correlation table, r = 0.26 is insignificant; but in the 'infert' correlation table, r = -0.21 is significant. I appreciate any insight into how this is calculated so I can better interpret my results.</p>
  
  <pre><code>library(sjPlot)
  
  ### Correlation table 1
  data("USArrests")
  my_data1 &lt;- data.frame(USArrests)
  sjt.corr(my_data1, corr.method = c("pearson"),fade.ns=TRUE,digits=2,use.viewer=FALSE)
  
  ### Correlation table 2 
  data("infert")
  my_data2 &lt;- data.frame(infert[2:7])
  sjt.corr(my_data2, corr.method = c("pearson"),fade.ns=TRUE,digits=2,use.viewer=FALSE)
  </code></pre>