The goal of circumplex is to provide a powerful, flexible, and user-friendly way to analyze and visualize circumplex data. It was created and is maintained by Jeffrey Girard; it was inspired by work from and was developed under advisement from Johannes Zimmermann and Aidan Wright. You can learn more about using this package through the vignette articles available on the package website or through ?circumplex.

Usage

data("jz2017")
results <- ssm_analyze(
  .data = jz2017, 
  scales = c(PA, BC, DE, FG, HI, JK, LM, NO), 
  angles = c(90, 135, 180, 225, 270, 315, 360, 45), 
  measures = c(NARPD, ASPD)
)
ssm_table(results)
Correlation-based Structural Summary Statistics with 95% CIs
Profile Elevation X-Value Y-Value Amplitude Displacement Fit
NARPD 0.20 [0.17, 0.24] -0.06 [-0.09, -0.03] 0.18 [0.15, 0.21] 0.19 [0.16, 0.22] 109.0 [99.2, 118.9] 0.957
ASPD 0.12 [0.09, 0.16] -0.10 [-0.13, -0.06] 0.20 [0.17, 0.24] 0.23 [0.19, 0.26] 115.9 [107.4, 124.4] 0.964
ssm_plot(results)

Code of Conduct

This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

References

Girard, J. M., Zimmermann, J., & Wright, A. G. C. (2018). New tools for circumplex data analysis and visualization in R. Meeting of the Society for Interpersonal Theory and Research. Montreal, Canada.

Zimmermann, J., & Wright, A. G. C. (2017). Beyond description in interpersonal construct validation: Methodological advances in the circumplex Structural Summary Approach. Assessment, 24(1), 3–23.

Wright, A. G. C., Pincus, A. L., Conroy, D. E., & Hilsenroth, M. J. (2009). Integrating methods to optimize circumplex description and comparison of groups. Journal of Personality Assessment, 91(4), 311–322.