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robumeta (version 2.1)

Robust Variance Meta-Regression

Description

Functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.

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Install

install.packages('robumeta')

Monthly Downloads

2,301

Version

2.1

License

GPL-2

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Last Published

March 28th, 2023

Functions in robumeta (2.1)

sensitivity

Sensitivity Analysis for Correlated Effects RVE
predict.robu

Prediction method for a robumeta object.
forest.robu

Forest Plots for Robust Variance Estimation Meta-Analysis
oswald2013

IAT Criterion-Related Correlations
oswald2013.ex1

IAT Criterion-Related Correlations
group.center

Convenience function for calculating group-centered covariates.
hierdat

Data for Fitting Hierarchical Effects Model
group.mean

Convenience function for calculating group-mean covariates.
hedgesdat

hedgesdat
print.robu

Outputs Model Information
robu

Fitting Robust Variance Meta-Regression Models
corrdat

Data for Fitting Correlated Effects Model
corrdat.sm

Data for Fitting Correlated Effects Model With Small-Sample Corrections