multibiasmeta: Sensitivity Analysis for Multiple Biases in Meta-Analyses
Meta-analyses can be compromised by studies' internal biases (e.g.,
confounding in nonrandomized studies) as well as by publication bias. This
package conducts sensitivity analyses for the joint effects of these biases
(per Mathur (2022) <doi:10.31219/osf.io/u7vcb>). These sensitivity analyses
address two questions: (1) For a given severity of internal bias across
studies and of publication bias, how much could the results change?; and
(2) For a given severity of publication bias, how severe would internal bias
have to be, hypothetically, to attenuate the results to the null or by a given
amount?
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
dplyr, EValue, metabias, metafor, purrr, Rdpack, rlang, robumeta |
| Suggests: |
glue, knitr, phacking, PublicationBias (≥ 2.3.0), rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2023-02-08 |
| Author: |
Mika Braginsky [aut, cre],
Maya Mathur [aut] |
| Maintainer: |
Mika Braginsky <mika.br at gmail.com> |
| BugReports: |
https://github.com/mathurlabstanford/multibiasmeta/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/mathurlabstanford/multibiasmeta,
https://mathurlabstanford.github.io/multibiasmeta/ |
| NeedsCompilation: |
no |
| Materials: |
README |
| In views: |
MetaAnalysis |
| CRAN checks: |
multibiasmeta results |
Documentation:
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