metacart-package {metacart}

R package for meta-CART

Description

In meta-analysis, heterogeneity often exists between studies. To understand this heterogeneity, researchers search for study characteristics (i.e., potential moderators) that may account for the variance in study effect sizes. When multiple potential moderators are available (e.g., intervention characteristics), traditional meta-analysis methods often lack sufficient power to investigate interaction effects between moderators, especially high-order interactions. To solve this problem, meta-CART was proposed by integrating Classification and Regression Trees (CART) into meta-analysis. The method idenfities the interaction effects between influential moderators, partitions the studies into more homogeneous subgroups, and estimates summary effect size in each subgroup. The fixed effect or random effects assumption can be consistently taken into account in both tree-growing process and subgroup analysis.

Details

Package:	metacart
Type:	Package
Version:	2.0-0
Date:	2018-11-12
License:	GPL

This method is suitable for identifying interaction effects between dichotomous, ordinal, continuous, and nominal moderators. The output of a REmrt object shows meta-CART analysis results based on the random effects model. And the output of a FEmrt object shows meta-CART analysis results based on the fixed effect model. The two objects display results for subgroup analysis including the Q-statistic and estimates for the subgroup effect sizes. Furthermore, the predict functions predict.REmrt and predict.FEmrt can be used to predict the effect size given the moderators. The plot functions plot.REmrt and plot.FEmrt show the interaction effects between identified moderators.

The core functions of the package are FEmrt and REmrt.

Author(s)

Maintainer: Xinru Li <[e-mail]>; Contributors: Elise Dusseldorp, Kaihua Liu (supported with the plot function), Jacqueline Meulman.

References

Dusseldorp, E., van Genugten, L., van Buuren, S., Verheijden, M. W., & van Empelen, P. (2014). Combinations of techniques that effectively change health behavior: Evidence from meta-cart analysis. Health Psychology, 33(12), 1530-1540. doi: 10.1037/hea0000018.

Li, X., Dusseldorp, E., & Meulman, J. J. (2017). Meta-CART: A tool to identify interactions between moderators in meta-analysis. British Journal of Mathematical and Statistical Psychology, 70(1), 118-136. doi: 10.1111/bmsp.12088.

Therneau, T., Atkinson, B., & Ripley, B. (2014) rpart: Recursive partitioning and regression trees. R package version, 4-1.

The articles of our own work can be found at http://www.elisedusseldorp.nl/

See Also

FEmrt, REmrt, summary.FEmrt,summary.REmrt, plot.FEmrt,plot.REmrt,predict.FEmrt,predict.REmrt