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It was created and is maintained by [Jeffrey Girard](https://jmgirard.com/), and was inspired by work from and was developed in conjunction with [Johannes Zimmermann](https://psychologische-hochschule.de/prof-dr-johannes-zimmermann/) and [Aidan Wright](https://personalityprocesses.com/). - -## 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. - -## Installation - -You can install the development version from [GitHub](https://github.com/) with: - -``` r -# install.packages("devtools") -devtools::install_github("jmgirard/circumplex") -``` - -## Examples of the Structural Summary Method (SSM) - -### Calculate correlation-based SSM parameters for multiple measures -```{r analysis1} -data("jz2017") -results <- ssm_analyze(jz2017, PA:NO, octants(), measures = c(NARPD, ASPD)) -``` - -``` r -ssm_table(results, xy = FALSE) -``` - -```{r table1, echo=FALSE} -ssm_table(results, xy = FALSE, render = FALSE) %>% - kable() %>% - kable_styling() -``` - - -```{r plot1} -ssm_plot(results) -``` - -### Calculate correlation-based SSM parameter contrast for two measures -```{r analysis2} -data("jz2017") -results <- ssm_analyze(jz2017, PA:NO, octants(), measures = c(NARPD, ASPD), - contrast = "test") -``` - -``` r -ssm_table(results, xy = FALSE) -``` - -```{r table2, echo=FALSE} -ssm_table(results, xy = FALSE, render = FALSE) %>% - kable() %>% - kable_styling() -``` - - -```{r plot2} -ssm_plot(results, xy = FALSE) -``` diff --git a/man/README.md b/man/README.md deleted file mode 100644 index e7f4e2a6..00000000 --- a/man/README.md +++ /dev/null @@ -1,167 +0,0 @@ - - -circumplex -=========================================================== - -[![Build Status](https://travis-ci.org/jmgirard/circumplex.svg?branch=master)](https://travis-ci.org/jmgirard/circumplex) [![Coverage status](https://codecov.io/gh/jmgirard/circumplex/branch/master/graph/badge.svg)](https://codecov.io/github/jmgirard/circumplex?branch=master) [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active) [![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing) - -Overview --------- - -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](https://jmgirard.com/), and was inspired by work from and was developed in conjunction with [Johannes Zimmermann](https://psychologische-hochschule.de/prof-dr-johannes-zimmermann/) and [Aidan Wright](https://personalityprocesses.com/). - -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. - -Installation ------------- - -You can install the development version from [GitHub](https://github.com/) with: - -``` r -# install.packages("devtools") -devtools::install_github("jmgirard/circumplex") -``` - -Examples of the Structural Summary Method (SSM) ------------------------------------------------ - -### Calculate correlation-based SSM parameters for multiple measures - -``` r -data("jz2017") -results <- ssm_analyze(jz2017, PA:NO, octants(), measures = c(NARPD, ASPD)) -``` - -``` r -ssm_table(results, xy = FALSE) -``` - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-Profile - -Elevation - -Amplitude - -Displacement - -Fit -
-NARPD - -0.20 [0.17, 0.23] - -0.19 [0.16, 0.22] - -109.0 [99.3, 118.4] - -0.957 -
-ASPD - -0.12 [0.09, 0.16] - -0.23 [0.19, 0.27] - -115.9 [107.4, 124.3] - -0.964 -
- -``` r -ssm_plot(results) -``` - -![](README-plot1-1.png) - -### Calculate correlation-based SSM parameter contrast for two measures - -``` r -data("jz2017") -results <- ssm_analyze(jz2017, PA:NO, octants(), measures = c(NARPD, ASPD), - contrast = "test") -``` - -``` r -ssm_table(results, xy = FALSE) -``` - - - - - - - - - - - - - - - - - - - - -
-Contrast - -Δ Elevation - -Δ Amplitude - -Δ Displacement - -Δ Fit -
-ASPD - NARPD - --0.08 [-0.12, -0.04] - -0.04 [-0.00, 0.07] - -7.0 [-3.5, 17.5] - -0.007 -
- -``` r -ssm_plot(results, xy = FALSE) -``` - -![](README-plot2-1.png)