bayestestR - Understand and Describe Bayesian Models and Posterior Distributions

Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.

Last updated 1 days ago

bayes-factorsbayesfactorbayesianbayesian-frameworkcredible-intervaleasystatshacktoberfesthdimapposterior-distributionsrope

16.85 score 580 stars 83 dependents 2.2k scripts 82k downloads

modelbased - Estimation of Model-Based Predictions, Contrasts and Means

Implements a general interface for model-based estimations for a wide variety of models, used in the computation of marginal means, contrast analysis and predictions. For a list of supported models, see 'insight::supported_models()'.

Last updated 16 hours ago

contrast-analysiscontrastseasystatsestimateggplot2hacktoberfestmarginalmarginal-effectsmeanspredict

12.44 score 244 stars 4 dependents 315 scripts 19k downloads

psycho - Efficient and Publishing-Oriented Workflow for Psychological Science

The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.

Last updated 4 years ago

apaapa6bayesiancorrelationformatinterpretationmixed-modelsneurosciencepsychopsychologyrstanarmstatistics

10.86 score 149 stars 5 dependents 628 scripts 1.7k downloads