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boot.heterogeneity

The package boot.heterogeneity implements a Bootstrap-Based Heterogeneity Test for standardized mean differences (d), Fisher-transformed Pearson’s correlations (r), and natural-logarithm-transformed odds ratio (OR) in Meta-Analysis Studies.

Depending on the presence of moderators, this Bootstrap-Based Test can be implemented in the random or mixed-effects model. This package uses rma() function from the R package metafor to obtain parameter estimates and likelihood, so installation of R package metafor is required.

Installation

You can install the released version of boot.heterogeneity from CRAN with:

install.packages("boot.heterogeneity")

And the development version from GitHub with:

# install.packages("devtools")
# library(devtools)
devtools::install_github("gabriellajg/boot.heterogeneity")

If you have already installed this package locally, you need to override the previous version with force installation:

devtools::install_github("gabriellajg/boot.heterogeneity", force = TRUE)

Updates to this package will always be pushed to Github first. If you encounter any errors, please re-install the package from github using force installation and try again.

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Install

install.packages('boot.heterogeneity')

Monthly Downloads

237

Version

1.1.5

License

GPL (>= 2)

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Maintainer

Ge Jiang

Last Published

October 23rd, 2021

Functions in boot.heterogeneity (1.1.5)

boot.d

Standardized Mean Differences (d): Bootstrap-based Heterogeneity Test for Between-study Heterogeneity in Random- or Mixed- Effects Model
boot.lnOR

Natural-Logarithm-Transformed Odds Ratio (lnOR): Bootstrap-based Heterogeneity Test for Between-study Heterogeneity in Random- or Mixed- Effects Model
boot.fcor

Fisher-transformed Pearson's correlation: Bootstrap-based Heterogeneity Test for Between-study Heterogeneity in Random- or Mixed- Effects Model