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orchaRd 2.0: An R package for visualizing meta-analyses with orchard plots

Shinichi Nakagawa, Malgorzata Lagisz, Rose E. O’Dea, Patrice Pottier, Joanna Rutkowska, Alistair M. Senior, Yefeng Yang, Daniel W. A. Noble

202326 citationsDOIOpen Access PDF

Abstract

1. Although meta-analysis has become an essential tool in ecology and evolution, reporting of meta-analytic results can still be much improved. To aid this, we have introduced the orchard plot, which presents not only overall estimates and their confidence intervals but also shows corresponding heterogeneity (as prediction intervals) and individual effect sizes. 2. Here, we have added significant enhancements by integrating many new functionalities as orchaRd 2.0. This updated version allows the visualisation of heteroscedasticity (different variances across levels of a categorical moderator), marginal estimates (e.g., marginalising out effects other than the one visualized), conditional estimates (i.e., estimates of different groups conditioned upon specific values of a continuous variable), and visualizations of all types of interactions between two categorical/continuous moderators.3. orchaRd 2.0 has additional functions which calculate key statistics from multilevel meta-analytic models such as I2 and R2. Importantly, orchaRd 2.0 contributes to better reporting by complying with PRISMA-EcoEvo (preferred reporting items for systematic reviews and meta-analyses in ecology and evolution). Taken together, orchaRd 2.0 can improve the presentation of meta-analytic results and facilitate the exploration of previously neglected patterns. 4. In addition, as a part of a literature survey, we found that graphical packages are rarely cited (~3%). We plea that researchers credit developers and maintainers of graphical packages, e.g., by citations in a figure legend, acknowledging the use of relevant packages.

Topics & Concepts

Categorical variableMeta-analysisOrchardComputer scienceStatisticsModerationEconometricsGraphicsPlot (graphics)HeteroscedasticityGeneralizability theoryEcologyMathematicsMachine learningBiologyMedicineComputer graphics (images)Internal medicineData Analysis with RSpecies Distribution and Climate ChangeEcology and Vegetation Dynamics Studies
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