Efficient and Publishing-Oriented Workflow for Psychological Science

psycho

Goal

The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to transform statistical outputs into something readable that can be, almost directly, copied and pasted into a report. It also implements various functions, from very useful ones (correlation(), normalize()) to miscellaenous ones (find_season()).

Contribute

Want to get involved in the developpment of an open-source software and improve psychological science? Join us!

• You need some help? You found a bug? You would like to request a new feature? Just open an issue :relaxed:

• Want to add a feature? Correct a bug? You're more than welcome to contribute!

• Looking for help to implement the analyze method for t.test, cor.test and anova.

Features

The psycho package can already do the following:

• Normalize your data
• Enlight you on how many factors to retain for a PCA
• Give you some clinically relevant info on a participant's score
• Compute complex correlation matrices
• Help you in the interpretation of various models (lme4, stan_lmer)

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")