orchaRd 2.0: An R package for visualising 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*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    53 Citations (Scopus)

    Abstract

    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. Here, we have added significant enhancements by integrating many new functionalities into 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 visualised), conditional estimates (i.e. estimates of different groups conditioned upon specific values of a continuous variable) and visualisations of all types of interactions between two categorical/continuous moderators. 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. 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, for example, by citations in a figure legend, acknowledging the use of relevant packages.

    Original languageEnglish
    Pages (from-to)2003-2010
    Number of pages8
    JournalMethods in Ecology and Evolution
    Volume14
    Issue number8
    DOIs
    Publication statusPublished - Aug 2023

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