Visualize 'confounder' control in meta-analysis.
'metaconfoundr' is an approach to evaluating bias in studies used in
meta-analyses based on the causal inference framework. Study groups
create a causal diagram displaying their assumptions about the
scientific question. From this, they develop a list of important
'confounders'. Then, they evaluate whether studies controlled for
these variables well. 'metaconfoundr' is a toolkit to facilitate this
process and visualize the results as heat maps, traffic light plots,
and more.
Version: |
0.1.2 |
Depends: |
R (≥ 3.5.0) |
Imports: |
dplyr (≥ 1.0.0), forcats, ggplot2 (≥ 3.4.0), magrittr, purrr, rlang (≥ 0.1.2), shiny, stringr, tibble, tidyr (≥
1.0.0), tidyselect |
Suggests: |
covr, knitr, metafor, patchwork, readr, rio, rmarkdown, roxygen2, spelling, testthat (≥ 3.0.0), vdiffr |
Published: |
2023-01-17 |
DOI: |
10.32614/CRAN.package.metaconfoundr |
Author: |
Malcolm Barrett
[aut, cre],
Julie M. Petersen
[aut],
Ludovic Trinquart
[aut] |
Maintainer: |
Malcolm Barrett <malcolmbarrett at gmail.com> |
BugReports: |
https://github.com/malcolmbarrett/metaconfoundr/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/malcolmbarrett/metaconfoundr |
NeedsCompilation: |
no |
Language: |
en-US |
Materials: |
README NEWS |
In views: |
MetaAnalysis |
CRAN checks: |
metaconfoundr results |