| Name | psycho |
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| Stable | |
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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 implements various useful functions with a special focus on the output, which becomes something readable that can be, almost directly, copied and pasted into a report or a manuscript.
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
☺️ - Want to add a feature? Correct a bug? You're more than welcome to contribute!
- Looking for help to implement and enhance the
analyzemethod for other models and tests.
Check examples in the following vignettes:
Or run the following:
library(rstanarm)
library(psycho)
df <- psycho::affective # Load a dataset from the psycho package
df <- standardize(df) # Standardize all numeric variables
fit <- stan_glm(Age ~ Salary, data=df) # Fit a Bayesian linear model
results <- analyze(fit) # Format the output
print(results)
summary(results)
plot(results)
contrasts <- get_contrasts(results, "Salary") # Compute estimated means and contrasts
contrasts$means
contrasts$contrasts
get_predicted(fit) # Get model predictionThe psycho package can already do the following:
- Standardize your data
- Enlight you on how many factors to retain for a PCA
- Give you some clinically relevant info on a participant's score
- Implements methods for single-case analyses
- Compute complex correlation matrices
- Compute signal detection theory indices (d', beta, ...)
- Help you in the interpretation of various models (mixed, Bayesian, ...)
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().
- 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")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 ;)