clinicalsignificance: A Toolbox for Clinical Significance Analyses in Intervention Studies

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.

Version: 2.0.0
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
Published: 2023-11-16
DOI: 10.32614/CRAN.package.clinicalsignificance
Author: Benedikt Claus ORCID iD [aut, cre]
Maintainer: Benedikt Claus <b.claus at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
In views: ClinicalTrials
CRAN checks: clinicalsignificance results


Reference manual: clinicalsignificance.pdf
Vignettes: Anchor-Based Approaches
Combined Approach
Distribution-Based Approach
Percentage-Change Approach to Clinical Significance in R
Statistical Approach


Package source: clinicalsignificance_2.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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_2.0.0.tgz
Old sources: clinicalsignificance archive


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