R package used to fit meta-regression models using robust
variance estimation (RVE) methods for correlated and hierarchical effects
models using the original (Hedges, Tipton and Johnson, 2010) and small-sample
corrected (Tipton, 2013) estimation methods.

The robumeta package provides a host of 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 in the robumeta package are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.

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 in the robumeta package are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.

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.

Zachary Fisher, Elizabeth Tipton, and Zhipeng Hou.

c(
person("Zachary","Fisher", email = "fish.zachary@gmail.com", role = c("aut", "cre")),
person("Elizabeth", "Tipton", role = "aut"),
person("Hou", "Zhipeng", role = "aut")
)
Zachary Fisher [aut, cre],
Elizabeth Tipton [aut],
Hou Zhipeng [aut]