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easystats: An R Framework for Easy Statistical Modeling, Visualization, and Reporting

easystats is a collection of R packages, which aims to provide a unifying and consistent framework to tame, discipline, and harness the scary R statistics and their pesky models.

However, there is not (yet) an unique "easystats" way of doing data analysis. Instead, start with one package and, when you'll face a new challenge, do check if there is an easystats answer for it in other packages. You will slowly uncover how using them together facilitates your life. And, who knows, you might even end up using them all.

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  1. datawizard Public

    Magic potions to clean and transform your data 🧙

    R 225 16

  2. bayestestR Public

    👻 Utilities for analyzing Bayesian models and posterior distributions

    R 582 57

  3. parameters Public

    📊 Computation and processing of models' parameters

    R 459 39

  4. performance Public

    💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

    R 1.1k 97

  5. effectsize Public

    🐉 Compute and work with indices of effect size and standardized parameters

    PostScript 345 24

  6. see Public

    🎨 Visualisation toolbox for beautiful and publication-ready figures

    R 914 43

Repositories

Showing 10 of 18 repositories
  • insight Public

    🔮 Easy access to model information for various model objects

    R 415 GPL-3.0 40 48 3 Updated Apr 24, 2025
  • parameters Public

    📊 Computation and processing of models' parameters

    R 459 GPL-3.0 39 49 3 Updated Apr 24, 2025
  • datawizard Public

    Magic potions to clean and transform your data 🧙

    R 225 16 27 7 Updated Apr 24, 2025
  • workflows Public

    GitHub Actions for {easystats} packages

    10 CC0-1.0 1 6 0 Updated Apr 24, 2025
  • dashboard Public

    Status of {easystats} packages

    HTML 4 1 2 0 Updated Apr 24, 2025
  • bayestestR Public

    👻 Utilities for analyzing Bayesian models and posterior distributions

    R 582 GPL-3.0 57 41 3 Updated Apr 23, 2025
  • modelbased Public

    📈 Estimate effects, contrasts and means based on statistical models

    R 243 GPL-3.0 21 19 2 Updated Apr 23, 2025
  • performance Public

    💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

    R 1,068 GPL-3.0 97 98 6 Updated Apr 22, 2025
  • effectsize Public

    🐉 Compute and work with indices of effect size and standardized parameters

    PostScript 345 24 17 (2 issues need help) 2 Updated Apr 20, 2025
  • correlation Public

    🔗 Methods for Correlation Analysis

    R 439 57 59 4 Updated Apr 18, 2025