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robumeta (version 2.0)

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

5,953

Version

2.0

License

GPL-2

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Maintainer

Zachary Fisher

Last Published

May 29th, 2017

Functions in robumeta (2.0)

group.mean

Convenience function for calculating group-mean covariates.
hedgesdat

hedgesdat
corrdat

Data for Fitting Correlated Effects Model
corrdat.sm

Data for Fitting Correlated Effects Model With Small-Sample Corrections
sensitivity

Sensitivity Analysis for Correlated Effects RVE
oswald2013.ex1

IAT Criterion-Related Correlations
predict.robu

Prediction method for a robumeta object.
forest.robu

Forest Plots for Robust Variance Estimation Meta-Analysis
group.center

Convenience function for calculating group-centered covariates.
hierdat

Data for Fitting Hierarchical Effects Model
oswald2013

IAT Criterion-Related Correlations
print.robu

Outputs Model Information
robu

Fitting Robust Variance Meta-Regression Models