Data Visualization for Statistics in Social Science
Plot regression models
Forest plot of multiple regression models
Summary of principal component analysis as HTML table
Summary of stacked frequencies as HTML table
Summary of contingency tables as HTML table
View structure of labelled data frames
Plot chi-squared distributions
Plot F distributions
Plot normal distributions
Plot t-distributions
Plot frequencies of variables
Plot grouped proportional tables
Arrange list of plots as grid
Plot grouped or stacked frequencies
Plot model fit from k-fold cross-validation
Plot likert scales as centered stacked bars
Plot predicted values and their residuals
Plot (grouped) scatter plots
Plot stacked proportional bars
Plot contingency tables
Save ggplot-figure for print publication
Set global theme options for sjp-functions
Plot One-Way-Anova tables
Plot Pearson's Chi2-Test of multiple contingency tables
Plot correlation matrix
Plot polynomials for (generalized) linear regression
Data Visualization for Statistics in Social Science
Modify plot appearance
Wrapper to create plots and tables within a pipe-workflow
Summary of correlations as HTML table
Print data frames as HTML table.
Summary of factor analysis as HTML table
Summary of item analysis of an item scale as HTML table
Print regression models as HTML table
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, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.