Efficient and Publishing-Oriented Workflow for Psychological Science
Clone or download
Permalink
Failed to load latest commit information.
.github blogpost + adapt get_contrasts to latest emmeans Jun 27, 2018
R Added ROPE to summary output Sep 20, 2018
data added emotion dataset Apr 12, 2018
docs typos in blogpost Aug 30, 2018
inst init Mar 21, 2018
man blogpost Aug 30, 2018
paper Update paper.md Jan 12, 2018
tests Major changes Aug 23, 2018
vignettes blogpost Aug 30, 2018
.Rbuildignore 0.2.6 Jun 1, 2018
.gitignore 0.1.0 Feb 5, 2018
.lintr added .lintr configuration (copied from corrplot R package) Oct 4, 2017
.travis.yml remove old from travis testing Apr 28, 2018
DESCRIPTION blogpost Aug 30, 2018
LICENSE init Mar 21, 2018
NAMESPACE Major changes Aug 23, 2018
NEWS.md Major changes Aug 23, 2018
README.md Update README.md Nov 14, 2018
appveyor.yml testing and stuff Jul 26, 2017
psycho.Rproj Init Jan 10, 2018

README.md

psycho logo r package

Efficient and Publishing-Oriented Workflow for Psychological Science

psycho

Build Status License: MIT CRAN downloads total Build status codecov Dependency Status CRAN downloads month HitCount

Name psycho
Stable CRAN
Documentation Rdoc
Blog
Examples
Questions
Authors
Reference DOI

Goal

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 by providing tools to format the output of statistical methods to directly paste them into a manuscript, ensuring standardization of statistical reporting.

Contribute

psycho is a young package in need of affection. You can easily hop aboard the developpment of this open-source software and improve psychological science:

  • Need some help? Found a bug? Request a new feature? Just open an issue ☺️
  • Want to add a feature? Correct a bug? You're more than welcome to contribute!

Don't be shy, try to code and submit a pull request (PR). Even if unperfect, we will help you to make a great PR! All contributors will be very graciously rewarded. Someday.

Examples

Check examples in the following vignettes:

Or blog posts:

General Workflow

The package revolves around the psychobject. Main functions from the package return this type, and the analyze() function transforms other R objects into psychobjects. Four functions can then be applied on a psychobject: summary(), print(), plot() and values().

Installation

  • To get the stable version from CRAN, run the following commands in your R console:
install.packages("psycho")
library("psycho")
  • To get the latest development version, run the following:
install.packages("devtools")
library("devtools")
install_github("neuropsychology/psycho.R")
library("psycho")

Credits

You can cite the package as following:

  • Makowski, (2018). The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science. Journal of Open Source Software, 3(22), 470. https://doi.org/10.21105/joss.00470

Please remember that psycho is a high-level package that heavily relies on many other packages, such as tidyverse, psych, qgraph, rstanarm, lme4 and others (See Description for the full list of dependencies). Please cite their authors ;)

Contributors