# Using 84% Confidence Intervals for testing differences in correlations

I would like to test the difference between 2 correlations on statistical significance by using confidence intervals.

Regarding means: By now I found out, that when comparing 2 means overlapping/non-overlapping 84% confidence intervals are close to a significance test at 5%, while computing 95% confidence intervals will be to conservative:

on stack exchange: Family-wise confidence intervals or ANCOVA in R suggests different intercepts, but the 95% CIs overlap... how is this possible? And here is a paper i found on google scholar regarding the comparision of means using an 84% confidence interval: https://academic.oup.com/jinsectscience/article/2577125

However, i couldn´t find anything regarding correlations.

So my question: Can i use a 84% confidence interval for testing correlations, just like it seems to be done with means?

• Perhaps this post stats.stackexchange.com/a/73628/128491 might be of help if I am understanding your question correctly. – Just_to_Answer Aug 5 '17 at 16:53
• That approach does not generalize from means to correlations. Why not compute the 95% confidence interval on the difference? Or, just test the significance of the difference directly. – David Lane Aug 5 '17 at 18:42
• thank you both for your answers. Mr. Lane answered my question by telling, that the 84% CI rule is not applicable for correlations. I will therefore simply calculate the 95% CI. – bucky Aug 6 '17 at 0:41