The concept of reliable and clinically significant change (Jacobson & Truax, 1991) helps you answer the following questions for a sample with two measurements at different points in time (pre & post): Which proportion of my sample has a (considering the reliability of the instrument) probably not-just-by-chance difference in pre- vs. post-scores? Which proportion of my sample does not only change in a statistically significant way (see question one), but also in a clinically significant way (e.g. change from a test score regarded "dysfunctional" to a score regarded "functional")? This package allows you to very easily create a scatterplot of your sample in which the x-axis maps to the pre-scores, the y-axis maps to the post-scores and several graphical elements (lines, colors) allow you to gain a quick overview about reliable changes in these scores. An example of this kind of plot is Figure 2 of Jacobson & Truax (1991). Referenced article: Jacobson, N. S., & Truax, P. (1991) <doi:10.1037/0022-006X.59.1.12>.
| Version: | 0.1.1 |
| Depends: | R (≥ 2.10) |
| Imports: | dplyr, ggplot2, stats, tibble |
| Published: | 2023-03-15 |
| DOI: | 10.32614/CRAN.package.rciplot |
| Author: | Maximilian Hagspiel [aut, cre, cph] |
| Maintainer: | Maximilian Hagspiel <maxhag at mailbox.org> |
| License: | MIT + file LICENSE |
| URL: | https://gitlab.com/REDS1736/rciplot |
| NeedsCompilation: | no |
| CRAN checks: | rciplot results |
| Reference manual: | rciplot.html , rciplot.pdf |
| Package source: | rciplot_0.1.1.tar.gz |
| Windows binaries: | r-devel: rciplot_0.1.1.zip, r-release: rciplot_0.1.1.zip, r-oldrel: rciplot_0.1.1.zip |
| macOS binaries: | r-release (arm64): rciplot_0.1.1.tgz, r-oldrel (arm64): rciplot_0.1.1.tgz, r-release (x86_64): rciplot_0.1.1.tgz, r-oldrel (x86_64): rciplot_0.1.1.tgz |
| Old sources: | rciplot archive |
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