---
title: "Interpolating the Inclusion of the Other in the Self Scale"
author: "Rémi Thériault"
date: "February 28, 2020"
output:
  rmarkdown::html_vignette:
    toc: true
    md_extensions: [ 
      "-autolink_bare_uris" 
    ]
vignette: >
  %\VignetteIndexEntry{Interpolating the Inclusion of the Other in the Self Scale}
  %\VignetteEngine{knitr::rmarkdown}
---

```{r, include=FALSE}
knitr::opts_chunk$set(fig.width = 6, fig.height = 6, warning = FALSE, 
                      message = FALSE, results = 'hide', out.width = "30%")
knitr::opts_knit$set(root.dir = tempdir())
```

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.

![](https://rempsyc.remi-theriault.com/images/blog_circles/IOS.png)

So through trial and error (using the `VennDiagram` package), I was able to determine the approximate actual overlap from the pictures (below).

![](https://rempsyc.remi-theriault.com/images//blog_circles/overlap.png)

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.


### Getting started

Load the `rempsyc` package:

```{r}
library(rempsyc)
```

> ***Note:*** If you haven't installed this package yet, you will need to install it via the following command: `install.packages("rempsyc")`.

### Score of 1 (0% overlap)

```{r}
overlap_circle(1)
```

### Score of 3.5 (25% overlap)

```{r}
overlap_circle(3.5)
```

### Score of 6.84 (81.8% overlap)

```{r}
overlap_circle(6.84)
```

## Changing labels

You can also change group labels with the `categories` argument, although 'Self' and 'Other' are the defaults.

```{r}
overlap_circle(3.12, categories = c("Humans","Animals"))
```

## Saving to file (PDF or PNG)
First save the plot to an object:

```{r}
plot <- overlap_circle(3.5)
```

Then you can use the ggplot2 save command directly with the object name:

```{r, eval = FALSE}
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 `.pdf` or `.eps` formats are recommended for scalable vector graphics for high-resolution submissions to scientific journals. However, you can also save in other formats, such as `.tiff`, `.png`, or `.jpg`.

## Example figure
This allowed me for instance, for one study (https://doi.org/10.1177/17470218211024826), to compare three of my groups side-by-side following an intervention:

![](https://rempsyc.remi-theriault.com/images//blog_circles/figure.png)

### Thanks for checking in
    
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](https://github.com/rempsyc/rempsyc/issues). See all tutorials here: [https://remi-theriault.com/tutorials](https://remi-theriault.com/tutorials).
