clinicalsignificance: Determine the Clinical Significance in Clinical Trials

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 as proposed by Jacobson et al., (1984) <doi:10.1016/S0005-7894(84)80002-7>.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: checkmate, crayon, dplyr, ggplot2, insight, lme4, magrittr, purrr, rlang, tibble, tidyr
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), tidyverse, vdiffr
Published: 2022-06-03
Author: Benedikt Claus ORCID iD [aut, cre]
Maintainer: Benedikt Claus <b.claus at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README
CRAN checks: clinicalsignificance results


Reference manual: clinicalsignificance.pdf
Vignettes: Clinical Significance Cutoffs
Clinical Significance Plots
Get started


Package source: clinicalsignificance_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): clinicalsignificance_1.0.0.tgz, r-oldrel (arm64): clinicalsignificance_1.0.0.tgz, r-release (x86_64): clinicalsignificance_1.0.0.tgz, r-oldrel (x86_64): clinicalsignificance_1.0.0.tgz


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