A clinical significance analysis can be used to determine if an intervention has a meaningful or practical effect for patients. You provide a tidy data set plus a few more metrics and this package will take care of it to make your results publication ready.
|Depends:||R (≥ 2.10)|
|Imports:||BayesFactor, bayestestR, cli, dplyr, ggplot2, insight, lme4, purrr, rlang, tibble, tidyr|
|Suggests:||knitr, rmarkdown, testthat (≥ 3.0.0), tidyverse, vdiffr|
|Author:||Benedikt Claus [aut, cre]|
|Maintainer:||Benedikt Claus <b.claus at pedscience.de>|
|License:||GPL (≥ 3)|
|CRAN checks:||clinicalsignificance results|
Percentage-Change Approach to Clinical Significance in R
|Windows binaries:||r-devel: clinicalsignificance_2.0.0.zip, r-release: clinicalsignificance_2.0.0.zip, r-oldrel: clinicalsignificance_2.0.0.zip|
|macOS binaries:||r-release (arm64): clinicalsignificance_2.0.0.tgz, r-oldrel (arm64): clinicalsignificance_2.0.0.tgz, r-release (x86_64): clinicalsignificance_2.0.0.tgz, r-oldrel (x86_64): clinicalsignificance_1.2.0.tgz|
|Old sources:||clinicalsignificance archive|
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