Interpolating the Inclusion of the Other in the Self Scale
February 28, 2020Source:
For anyone in social psychology using the Inclusion of the Other in the Self (IOS) Scale to measure self-other merging, you might have wished that you could know for sure how much self-other overlap there is between your participant and a target group or individual.
Indeed, the IOS response choices go from 1 to 7 only, and unfortunately these don’t match the percentage overlap from the circle images (i.e., 1/7 is not 14% overlap, and 7/7 is not 100% overlap). You can observe this on the original IOS scale below.
So through trial and error (using the
package), I was able to determine the approximate actual overlap from
the pictures (below).
I feel like the overlap is pretty close to the original scale. Based
on this, I used the
approx() function to interpolate any
responses so that 1 = 0% (overlap), 2 = 10%, 3 = 20%, 4 = 30%, 5 = 55%,
6 = 65%, and 7 (the maximum) = 85%.
But that also means that a continuous response (for example based on a group average) can also be plotted accurately (e.g., a score of 6.84 would turn into 81.8 % overlap). Let’s see a few examples.
Note: If you haven’t installed this package yet, you will need to install it via the following command:
You can also change group labels with the
argument, although ‘Self’ and ‘Other’ are the defaults.
First save the plot to an object:
plot <- overlap_circle(3.5)
Then you can use the ggplot2 save command directly with the object name:
ggplot2::ggsave(plot, file = "overlap.pdf", width = 7, height = 7, unit = 'in', dpi = 300) # Change the path to where you would like to save it. # If you copy-paste your path name, remember to # use "R" slashes ('/' rather than '\'). # Also remember to specify the .pdf extension of the file.
Pro tip: Recommended dimensions for saving is 7 inches wide and 7 inches high. The
.epsformats are recommended for scalable vector graphics for high-resolution submissions to scientific journals. However, you can also save in other formats, such as
This allowed me for instance, for one study, to compare three of my groups side-by-side following an intervention:
Make sure to check out this page again if you use the code after a time or if you encounter errors, as I periodically update or improve the code. Feel free to contact me for comments, questions, or requests to improve this function at https://github.com/rempsyc/rempsyc/issues. See all tutorials here: https://remi-theriault.com/tutorials.