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psycModel

Integrated Toolkit for Psychological Analysis and Modeling in R

Installation

CRAN Stable Version

# Install the standard version 
install.packages('psycModel')

# Install all of the suggested dependencies for full functionality 
install.packages('psycModel',dependencies = c("Depends", "Imports","Suggests")) 

Dev Version (newest feature)

devtools::install_github('jasonmoy28/psycModel')

Key Features

A beginner-friendly R package for statistical analysis in social science (intermediate & advanced R users should also find it useful) Tired of manually writing all variables in a model? You can use dplyr::select() syntax for all models Produce publication-ready tables and figures (e.g., descriptive table) Fitting models, plotting, checking goodness of fit, and model assumption violations all in one place. Beautiful and easy-to-read output. Check out this example now.

Supported Models

Regression models:

  • Linear regression (i.e., support ANOVA, ANCOVA) & curvilinear regression
  • Linear mixed effect model (i.e., HLM, MLM).

Structure Equation Modeling:

  • Exploratory & confirmatory factor analysis
  • Measurement invariance (MGCFA approach)
  • Mediation analysis (SEM approach)

Other:

  • Descriptive statistics
  • Correlation
  • Reliability analysis

Note: If you like this package, please considering give it a star. I would really appreciate that. If you experience any problem, please feel free to open a new issue here

Credit

Authors: Jason Moy

Citation: Moy, J. H. (2021). psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R. CRAN. https://cran.r-project.org/package=psycModel.

Logo Design: Danlin Liu

Disclaimer:

The current release is the alpha version of the package since I plan to add more features and support more models in the future (read more about planned updates here). If you are interested in help building this package, please feel free to submit a pull request / GitHub issue. Although I tried my best to fix any bugs, the package is not guarantee to be bug-free. If you find any bugs, please submit them in the GitHub issue. This package is licensed under the GPLv3 liscense. You may use, re-distribute, and modified the package. Additionally, this package does provide any kind of warranty, either expressed or implied based on the GPLv3 liscense. Finally, you should expect many changes that are not backward compatible until the package's first major release (i.e., v1.0.0).

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Version

Install

install.packages('psycModel')

Monthly Downloads

310

Version

0.5.0

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Jason Moy

Last Published

November 1st, 2023

Functions in psycModel (0.5.0)

lme_model

Linear Mixed Effect Model
model_summary

Model Summary for Regression Models
two_way_interaction_plot

Two-way Interaction Plot
tidyeval

Tidy eval helpers
lme_multilevel_model_summary

Model Summary for Mixed Effect Model
reliability_summary

Reliability Analysis
print_table

print_table (internal use only)
lm_model_summary

Model Summary for Linear Regression
%>%

Pipe operator
lm_model_table

Linear Regression Model Table Generate tables with multiple response and predictor variable (only lm models are supported)
lm_model

Linear Regressions / ANOVA / ANCOVA
two_way_interaction_terms

Interaction term for Mixed Effect Model (internal use only) Create interaction terms for regression models
simple_slope

Slope Estimate at Varying Level of Moderators
three_way_interaction_plot

Three-way Interaction Plot
text_convert

text_convert for super_print (internal use only)
popular

Popular dataset
super_print

super_print (internal use only)
polynomial_regression_plot

Polynomial Regression Plot
mediation_summary

Mediation Analysis
measurement_invariance

Measurement Invariance
cronbach_alpha

Cronbach alpha
descriptive_table

Descriptive Statistics Table
coefficent_to_p

change coefficient to p value for model_table
compare_fit

Comparison of Model Fit
cfa_summary

Confirmatory Factor Analysis
cfa_groupwise

Confirmatory Factor Analysis (groupwise)
efa_summary

Exploratory Factor Analysis
anova_plot

ANOVA Plot
cor_test

Correlation table
data_check

Data Check (internal use only)
html_to_pdf

Convert HTML to PDF
get_interaction_term

get interaction term
label_name

get label name
interaction_plot

Interaction plot
knit_to_Rmd

Knit Rmd Files Instruction
format_round

Format digits (internal use only)
interaction_check

interaction_check
get_predict_df

get factor df to combine with mean_df
glm_model

Generalized Linear Regression