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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.

psycho logo r package

Efficient and Publishing-Oriented Workflow for Psychological Science

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

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

News

Current Dev

0.4.0 (2018-06-11)

Breaking changes

  • Major release, lots of undocumented breaking changes.)
  • Changed hdi to HDI
  • Removed Mean and SD from summary in bayes_cor.test

New functions / parameters

  • Added simulate_data_regression
  • Extended standardize method
  • Added get_R2 method
  • Added interpret_odds and logistic regression effect size interpretation
  • Added omega_sq and interpret_omega_sq

Changes

  • Enhance print for analyze.aov

0.2.8 (2018-06-11)

Breaking changes

  • Renamed bayesian_cor to bayes_cor for consistency
  • Changed parameters name and role in refdata
  • Changed output of analyze.stanreg
  • effsize in analyze.stanreg default to TRUE
  • Fixed bug in dprime

New functions / parameters

  • Added interpret_RMSEA
  • Added analyze.lavaan and analyze.aov
  • Added remove_empty_cols
  • Added model_to_priors
  • First iteration on custom rule's sets for effects sizes
  • Added analyze.htest for correlations and t-tests
  • Added interpret_R2
  • Added "bayesian" method for correlation matrix
  • Added reorder_matrix
  • Added bayes_adj_R2 for loo-adjusted R2 in stanreg models
  • Added get_std_posteriors for standardized coefs in Bayesian models
  • First iteration on bayesian_cor for Bayesian correlation tables
  • Added standardized coefs computation to analyze.stanreg
  • Added refdata for reference grid creation
  • Added rope for region of practical equivalence
  • Added interpret_r for correlation coefficient interpretation
  • Added bayesian_cor.test, start to work on implementation of bayesian method for correlation
  • Added find_matching_string for fuzzy string matching
  • Added analyze for psych::fa objects

Changes

  • Improvements on analyze.stanreg

0.2.3 (2018-05-11)

Breaking changes

  • mellenbergh.test, crawford.test and crawford.test.freq now return a psychobject
  • assess has been refactored to become a wrapper for crawford.test
  • crawford.test now computes the Bayesian version
  • crawford.test has been renamed to crawford.test.freq

New functions / parameters

  • Added i_am_cheating parameter to correlation to prevent p-hacking
  • Added percentile and percentile_to_z functions
  • Added as.data.frame method for density objects
  • Added Crawford-Garthwaite (2007) Bayesian test for single-case analysis
  • Added rnorm_perfect function

Changes

  • Improvements on analyze.stanreg
  • Fixed draws parameter in get_predicted.stanreg
  • logo

0.2.0 (2018-05-01)

Breaking changes

  • Set default overlap parameter to TRUE in analyze.stanreg
  • Remove support of lmerMod objects (linear mixed models must be fitted with lmerTest)
  • Refactored get_predicted.stanreg
  • Changed organization of values in analyzed models
  • Added subset parameter in standardize
  • Changed order of parameters in dprime

New functions / parameters

  • Added print for n_factors
  • Added overlap (experimental) parameter to analyze.stanreg as a different index of effect existence
  • Added overlap function
  • Added power_analysis function.
  • Added analyze.lm for lm objects.
  • Added interpret_bf for bayes factor interpretation
  • Added probs_to_odds
  • Added confidence intervals (CI) to analyze for lmerTest models
  • Refactored odds_to_probs
  • Added ìs.mixed.stanreg`
  • Added keep_iterations in get_predicted.stanreg (and demonstration of how to plot them in vignettes)
  • Added emotion dataset
  • Added get_contrasts methods for lme4 objects
  • Added prior info in analyze.stanreg
  • Added (exposed) interpret_d_posterior for Bayesian size effect interpretation
  • Added find_combinations function
  • Added find_best_model function
  • Added is.standardized function
  • Added get_contrasts.stanreg and get_predicted.stanreg functions
  • Added crawford_dissociation.test function for single-case tests
  • Externalized the "mpe" function
  • Added affective dataset

Changes

  • Added model selection chapter in Bayesian vignettes
  • Refactor the analyze.stanreg code
  • Improved standardize for vectors
  • Added random effects summary in analyze.stanreg
  • Improved mellenbergh.test
  • Improved analyze.stanreg
  • Added new vignette for "Bayesian analyses in psychology"
  • Improved crawford.test

0.1.4 (2018-03-23)

Breaking changes

New functions / parameters

  • Added R2 for bayesian regressions
  • Added dprime function for signal detection theory indices computation
  • Added crawford.test and mellenbergh.test function for single-case tests
  • Added get_predicted for stanreg models

Changes

0.1.0 (2018-02-05)

Breaking changes

  • normalize has been renamed to standardize #30

New functions / parameters

  • Added support to lme4's merMod objects
  • Added print output to correlation
  • Added glasso and cor_auto estimation for correlation #25 #24
  • added is.psychobject function.

Changes

  • CRAN release
  • Fixed #28
  • Nicer print.psychobject output #32
  • Replaced NAs by empty strings in correlation #23

0.0.8 (2018-01-04)

Breaking changes

New functions / parameters

Major changes

Minor changes

  • Added CONTRIBUTING.md
  • Changed format_digit
  • Added except parameter to normalize

0.0.7 (2018-01-10)

Breaking changes

New functions / parameters

Major changes

Minor changes

  • Changed format_digit
  • Added except parameter to normalize

0.0.6 (2017-12-07)

Breaking changes

New functions / parameters

  • HDI: Compute highest density intervals
  • format_string: A tidyverse friendly version of sprintf

Major changes

  • Changed credible interval computation in analyze.stanreg

Minor changes

  • Use styler

0.0.4 (2017-11-15)

Breaking changes

New functions / parameters

  • correlation: Plot is now supported by ggcorrplot instead of corrplot. The function behaves consistently (plot(correlation(df))

Major changes

  • correlation: Fix p values adjustment

Minor changes

  • analyze.stanreg: Removed the mean and sd of the print(), added the MPE
  • analyze.stanreg: Returns features of R2 for stan_lm

0.0.3 (2017-11-10)

Breaking changes

New functions / parameters

  • n_factors: How many factors to retain for PCA or factor analysis?

Major changes

Minor changes

0.0.2 (2017-10-12)

Breaking changes

New functions / parameters

  • analyze.merModLmerTest
  • analyze.glmerMod

Major changes

Minor changes

  • Improve testing

0.0.1 (2017-10-06)

Breaking changes

New functions / parameters

Major changes

  • First CRAN release

Minor changes

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.
install.packages("psycho")

0.5.0 by Dominique Makowski, a month ago

https://github.com/neuropsychology/psycho.R

Report a bug at https://github.com/neuropsychology/psycho.R/issues

Browse source code at https://github.com/cran/psycho

Authors: Dominique Makowski [aut, cre, cph] , Hugo Najberg [ctb] , Viliam Simko [ctb] , Sasha Epskamp [rev] (Sasha reviewed the package for JOSS , see https://github.com/openjournals/joss-reviews/issues/470)

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports methods, stats, scales, utils, dplyr, tidyr, stringr, ggplot2, insight, bayestestR, parameters, performance, effectsize

Suggests knitr, rmarkdown, testthat, covr, plotly, GPArotation

Imported by CLUSTShiny, KNNShiny, PREPShiny, STAT.

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