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metacart (version 3.0.4)

Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis

Description

Meta-CART integrates classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The method is described in Dusseldorp et al. (2014) and Li et al. (2017) .

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Version

Install

install.packages('metacart')

Monthly Downloads

244

Version

3.0.4

License

GPL (>= 2)

Maintainer

Juan Claramunt Gonzalez

Last Published

August 18th, 2025

Functions in metacart (3.0.4)

dat.BCT2009

A subset of data from Michie et al. (2009)
rcpp_hello_world

Simple function using Rcpp
treepruner

Prune a tree
updateNodes

A function to update node
re.cutoff_cpp

A function to find the split point
summary.FEmrt

Summary of the results of a FE meta-tree object
plot.REmrt

Visualisation of a RE meta-tree
summary.REmrt

Summary of the results of a RE meta-tree object
plot.FEmrt

Visualisation of a FE meta-tree
.compute_re_Q_

Compute re Q for different values of tau2
print.REmrt

Print function for REmrt
print.FEmrt

Print function for FEmrt
predict.FEmrt

Predictions from a fitted FE metacart object
plotPV

Visualization of a initial RE meta-tree with frequency coloring
find_second_split

A function to find the optimal combination of first two splits, and the corresponding Q-between given the first split
permuteRE

Permutation test
dat.balanced

A simulated meta-analytic data set with balanced pure interaction effects
oval_draw

A function to draw an oval
metacart-package

R package for meta-CART
.ReplaceNA

Replace missing values by the overall weighted mean
permuteFE

A function returns the Q-between from the tree with given size
predict.REmrt

Predictions from a fitted RE metacart object
prednode_cpp

A function to predict newdata based on the fitted model
BootCI

This functions performs bootstrap to compute the confidence intervals for the subgroup effect size estimates. This function is only applicable to Random effects metaregression trees with 2 terminal nodes or more.
Q_selected_size_GS

A function returns the Q-between from the tree with given size
REmrt

Random effects meta-tree
FEmrt

Fixed effect meta-tree
.PredY

Predict effect size for the test set
compute_rebetQ

A function to compute RE Q-between
REmrt_SSS

A function to fit the tree with look-ahead option
CI_draw

A function to draw the confidence interval as a diamond
Xvalid_all

A function to compute cross-validation errors
REmrt_GS_

A function to fit the tree with look-ahead option
SimData

A simulated meta-analytic data set
find_triplet

A function to find the best triplets of parent, moderator, and split point.
computetableIT

A function to compute table for initial tree
computetable

A function to compute table
.ComputeY

Compute the subgroup effect sizes
.compute_tau_

Compute tau2
make_first_split

A function to list all possible split points for the first split
.partition

Partition the test set based on a trained tree
encodeHtml

A function to deal with symbols