ArticleBehavior research methods2025
Informative data visualization with raincloud plots in JASP.
Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Proper data visualization helps researchers draw correct conclusions from their data and facilitates a more complete and transparent report of the results. In factorial designs, so-called raincloud plots have recently attracted attention as a particularly informative data visualization technique; raincloud plots can simultaneously show summary statistics (i.e., a box plot), a density estimate (i.e., the cloud), and the individual data points (i.e., the raindrops). Here we first present a 'raincloud quartet' that underscores the added value of raincloud plots over the traditional presentation of means and confidence intervals. The added value of raincloud plots appears to be increasingly recognized: a focused literature review of plots in Psychonomic Bulletin & Review shows that 9% of plots in 2023 were raincloud plots. Another 29% of plots (vs. 2% in 2013) contained individual data points (i.e., raindrops), indicating a strong trend towards transparent and informative data visualization. To further encourage this trend and make raincloud plotting easy and practical for a broader group of researchers and students, we implemented a comprehensive suite of raincloud plots in JASP, an open-source statistics program with an intuitive graphical user interface. Examples from two factorial research designs illustrate how the JASP raincloud plots support a correct and comprehensive interpretation of the data.
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