pcir

Developing a R package called ‘Potential for Conflict Index - PCI’, which is a descriptive statistical method used to enhance the understanding of outcomes in human dimensions research. The package will equip users with the tools required for calculating, comparing, and graphing the potential for conflict.

https://github.com/fblpalmeira/pcir

Repository

Developing a R package called ‘Potential for Conflict Index - PCI’, which is a descriptive statistical method used to enhance the understanding of outcomes in human dimensions research. The package will equip users with the tools required for calculating, comparing, and graphing the potential for conflict.

README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = '#>',
  fig.path = 'man/figures/logo_pcir.png',
  out.width = '100%',
  eval = TRUE)

library(pcir)
```

# pcir: Potential for Conflict Index in R 

## Overview

`pcir` is an R package developed to assist researchers and practitioners in calculating,
comparing, and visualizing the Potential for Conflict Index (PCI) among stakeholders.
PCI is a descriptive statistical method designed to enhance the understanding of
outcomes in human dimensions research [(Manfredo et al. 2003;](https://www.tandfonline.com/doi/abs/10.1080/10871200304310)
[Vaske et al. 2010)](https://www.tandfonline.com/doi/abs/10.1080/01490401003712648).

The concepts of consensus, disagreement, and conflict are relevant across a wide
range of disciplines, including economics, political science, psychology,
sociology, and natural resource management. Although PCI can be calculated using
software such as Excel, SPSS, and SAS, no dedicated R package existed for this
analysis — until now.

This package was developed as part of my training in the
[rOpenSci Champions Program](https://ropensci.org/champions/),
supported by the Chan Zuckerberg Initiative.

Additional information:

- [Introducing rOpenSci Champions - Cohort 2023-2024](https://ropensci.org/blog/2024/02/15/champions-program-champions-2024/)

## Theoretical approach



**Figure 1.** Likert scales used in the Potential for Conflict Index (PCI).

## Workflow

Steps implemented in the 'pcir' package:

 1. Read the input data from interviews – see example dataset [(Spreadsheet)]();

 2. Count the frequency of responses for each question – see [(Table 1)]();

 3. Calculate the PCI for each question – see [(Table 2)]();

 4. Generate a bubble chart to visualize the results – see [(Figure)]().



**Figure 2.** Workflow of the `pcir` package.

## Features

- `counting()`: Summarizes data by calculating counts, percentages, means, and standard deviations.

- `pci()`: Computes the Potential for Conflict Index from summary data.

- `bubble()`: Visualizes PCI results using a bubble plot.

## Installation

Install the development version of `pcir` directly from GitHub:

```r
# Uncomment the line below if devtools is not installed
# install.packages("devtools")

devtools::install_github("fblpalmeira/pcir")
```

## Usage

After installation, load the package:

```r
library(pcir)
```

Example dataset:

```r
df1 <- data.frame(
  A = c(-1, -1, -1, 0, -1),
  B = c(-1, 1, 0, -1, 1),
  C = c(0, 0, 1, 0, -1),
  D = c(0, -1, 1, 1, 1),
  E = c(1, 1, 0, -1, -1)
)
```

Count responses:

```r
data <- counting(df1, cols = names(df1)[2:6])
data
```

Calculate PCI:

```r
data <- pci(data,
                 scale_type = 'bipolar_with_neutral',
                 min_scale_value = -1,
                 max_scale_value = 1)
```

Visualize with a bubble plot:

```r
# The bubble function creates a bubble plot to visualize the PCI results.
# You can customize the colors and title as per your preferences.
plot <- bubble(data = df3,
               scale_type = 'bipolar_with_neutral',
               ylim_range = 3,
               bubble_color = 'lightblue',
               bubble_stroke = 'darkblue',
               title = 'Custom Bubble Colors')
plot

```



**Figure 3.** Bubble chart illustrating the Potential for Conflict Indices.

## References

Manfredo, M., Vaske, J., Teel, T. (2003). [The potential for conflict index: A
graphic approach to practical significance of human dimensions research](https://www.tandfonline.com/doi/abs/10.1080/10871200304310).
Human Dimensions of Wildlife, 8(3), 219-228.

Vaske, J. J., Beaman, J., Barreto, H., Shelby, L. B. (2010). [An extension and
further validation of the potential for conflict index](https://www.tandfonline.com/doi/abs/10.1080/01490401003712648).
Leisure Sciences, 32(3), 240-254.

## Citation

If you use the `pcir` package in your work, please cite it as follows:

```r
citation(package = 'pcir')
```

Example output:

```r
To cite the 'pcir' package in publications, use:

  Palmeira F, Wundervald B (2025). _pcir: Potential for
  Conflict Index in R_. R package version 0.0.0.9000,
  .

The BibTeX entry for LaTeX users is

  @Manual{,
    title = {pcir: Potential for Conflict Index in R},
    author = {Francesca Belem Lopes Palmeira and Bruna Wundervald},
    year = {2025},
    note = {R package version 0.0.0.9000},
    url = {https://github.com/fblpalmeira/pcir},
  }
```

## License

This package is licensed under the [MIT License](https://github.com/fblpalmeira/pcir?tab=MIT-1-ov-file) file for more details.

## Bug Reports

If you encounter any bugs or issues, please report them on the [GitHub Issues](https://github.com/fblpalmeira/pcir/issues) page.

Note: To report a bug, you need a GitHub account, which you can join for free.

## Discussions

The [Discussions section](https://github.com/fblpalmeira/pcir/discussions) is the space for the `pcir` community  to ask questions,
share ideas, or get help without opening formal issues.

## Contact

For any questions or inquiries, please contact Francesca Palmeira at
francesca@alumni.usp.br.

Owner

Citation (citation.txt)

list(title = "pcir: Potential for Conflict Index in R", author = list(list(given = "Francesca Belem Lopes", family = "Palmeira", role = c("aut", "cre"), email = "francesca@alumni.usp.br", comment = c(ORCID = "0000-0002-7597-1157")), list(given = "Bruna", family = "Wundervald", role = "aut", email = "brunadaviesw@gmail.com", comment = c(ORCID = "0000-0001-8163-220X"))), year = "2025", note = "R package version 0.0.0.9000, commit 5e6e136d96ae2502b5f7f35d6f78977a3d7bc689", url = "https://github.com/fblpalmeira/pcir")

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