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multibiasmeta  

Sensitivity Analysis for Multiple Biases in Meta-Analyses
View on CRAN: Click here


Download and install multibiasmeta package within the R console
Install from CRAN:
install.packages("multibiasmeta")

Install from Github:
library("remotes")
install_github("cran/multibiasmeta")

Install by package version:
library("remotes")
install_version("multibiasmeta", "0.2.2")



Attach the package and use:
library("multibiasmeta")
Maintained by
Peter Solymos
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-02-08
Latest Update: 2023-08-23
Description:
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) ). 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?
How to cite:
Peter Solymos (2023). multibiasmeta: Sensitivity Analysis for Multiple Biases in Meta-Analyses. R package version 0.2.2, https://cran.r-project.org/web/packages/multibiasmeta. Accessed 31 Jan. 2025.
Previous versions and publish date:
0.1.0 (2023-02-08 10:40), 0.2.0 (2023-08-18 20:32), 0.2.1 (2023-08-21 11:22)
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Complete documentation for multibiasmeta
Functions, R codes and Examples using the multibiasmeta R package
Some associated functions: meta_meat . multibias_evalue . multibias_meta . multibiasmeta-package . 
Some associated R codes: data.R . evalue.R . meta.R . metabias-names.R . multibiasmeta-package.R .  Full multibiasmeta package functions and examples
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