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sjPlot - Data Visualization for Statistics in Social Science

Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, PCA and correlation matrices, cluster analyses, scatter plots, Likert scales, effects plots of interaction terms in regression models, constructing index or score variables and much more.

Installation

Latest development build

To install the latest development snapshot (see latest changes below), type the following commands into the R console:

library(devtools)
devtools::install_github("strengejacke/sjPlot")

Official, stable release

To install the latest stable release from CRAN, type the following command into the R console:

install.packages("sjPlot")

Documentation and examples

Please visit https://strengejacke.github.io/sjPlot/ for documentation and vignettes.

Citation

In case you want / have to cite my package, please use citation('sjPlot') for citation information. Since core functionality of package depends on the ggplot-package, consider citing this package as well.

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Version

Install

install.packages('sjPlot')

Monthly Downloads

35,297

Version

2.8.17

License

GPL-3

Maintainer

Last Published

November 29th, 2024

Functions in sjPlot (2.8.17)

set_theme

Set global theme options for sjp-functions
plot_likert

Plot likert scales as centered stacked bars
save_plot

Save ggplot-figure for print publication
plot_model

Plot regression models
plot_scatter

Plot (grouped) scatter plots
sjPlot-package

Data Visualization for Statistics in Social Science
plot_xtab

Plot contingency tables
plot_models

Forest plot of multiple regression models
plot_stackfrq

Plot stacked proportional bars
plot_residuals

Plot predicted values and their residuals
sjp.poly

Plot polynomials for (generalized) linear regression
sjplot

Wrapper to create plots and tables within a pipe-workflow
sjp.aov1

Plot One-Way-Anova tables
sjp.chi2

Plot Pearson's Chi2-Test of multiple contingency tables
sjPlot-themes

Modify plot appearance
tab_fa

Summary of factor analysis as HTML table
tab_corr

Summary of correlations as HTML table
sjp.corr

Plot correlation matrix
tab_df

Print data frames as HTML table.
tab_itemscale

Summary of item analysis of an item scale as HTML table
view_df

View structure of labelled data frames
tab_stackfrq

Summary of stacked frequencies as HTML table
tab_xtab

Summary of contingency tables as HTML table
tab_model

Print regression models as HTML table
tab_pca

Summary of principal component analysis as HTML table
plot_kfold_cv

Plot model fit from k-fold cross-validation
dist_t

Plot t-distributions
dist_f

Plot F distributions
dist_norm

Plot normal distributions
efc

Sample dataset from the EUROFAMCARE project
plot_grid

Arrange list of plots as grid
plot_gpt

Plot grouped proportional tables
dist_chisq

Plot chi-squared distributions
plot_frq

Plot frequencies of variables
plot_grpfrq

Plot grouped or stacked frequencies