Function reference • sjPlot

All functions
`dist_chisq()`	Plot chi-squared distributions
`dist_f()`	Plot F distributions
`dist_norm()`	Plot normal distributions
`dist_t()`	Plot t-distributions
`efc`	Sample dataset from the EUROFAMCARE project
`plot_grid()`	Arrange list of plots as grid
`plot_model()` `get_model_data()`	Plot regression models
`plot_models()`	Forest plot of multiple regression models
`save_plot()`	Save ggplot-figure for print publication
`set_theme()`	Set global theme options for sjp-functions
`sjc.cluster()`	Compute hierarchical or kmeans cluster analysis
`sjc.dend()`	Compute hierarchical cluster analysis and visualize group classification
`sjc.elbow()`	Compute elbow values of a k-means cluster analysis
`sjc.grpdisc()`	Compute a linear discriminant analysis on classified cluster groups
`sjc.kgap()`	Compute gap statistics for k-means-cluster
`sjc.qclus()`	Compute quick cluster analysis
`sjp.aov1()`	Plot One-Way-Anova tables
`sjp.chi2()`	Plot Pearson's Chi2-Test of multiple contingency tables
`sjp.corr()`	Plot correlation matrix
`sjp.fa()`	Plot FA results
`sjp.frq()`	Plot frequencies of variables
`sjp.glm()`	Plot estimates, predictions or effects of generalized linear models
`sjp.glmer()`	Plot estimates, predictions or effects of generalized linear mixed effects models
`sjp.gpt()`	Plot grouped proportional tables
`sjp.grpfrq()`	Plot grouped or stacked frequencies
`sjp.int()`	Plot interaction effects of (generalized) linear (mixed) models
`sjp.kfold_cv()`	Plot model fit from k-fold cross-validation
`sjp.likert()`	Plot likert scales as centered stacked bars
`sjp.lm()`	Plot estimates, predictions or effects of linear models
`sjp.lmer()`	Plot estimates, predictions or effects of linear mixed effects models
`sjp.pca()`	Plot PCA results
`sjp.poly()`	Plot polynomials for (generalized) linear regression
`sjp.resid()`	Plot predicted values and their residuals
`sjp.scatter()`	Plot (grouped) scatter plots
`sjp.stackfrq()`	Plot stacked proportional bars
`sjp.xtab()`	Plot contingency tables
`sjPlot-package`	Data Visualization for Statistics in Social Science
`theme_sjplot()` `theme_sjplot2()` `theme_blank()` `theme_538()` `font_size()` `label_angle()` `legend_style()` `scale_color_sjplot()` `scale_fill_sjplot()` `sjplot_pal()` `show_sjplot_pals()`	Modify plot appearance
`sjplot()` `sjtab()`	Wrapper to create plots and tables within a pipe-workflow
`sjt.corr()`	Summary of correlations as HTML table
`sjt.fa()`	Summary of factor analysis as HTML table
`sjt.frq()`	Summary of frequencies as HTML table
`sjt.glm()`	Summary of generalized linear models as HTML table
`sjt.glmer()`	Summary of generalized linear mixed models as HTML table
`sjt.grpmean()` `sjt.df()` `sjt.mwu()`	Deprecated functions
`sjt.itemanalysis()`	Summary of item analysis of an item scale as HTML table
`sjt.lm()`	Summary of linear regression as HTML table
`sjt.lmer()`	Summary of linear mixed effects models as HTML table
`sjt.pca()`	Summary of principal component analysis as HTML table
`sjt.stackfrq()`	Summary of stacked frequencies as HTML table
`sjt.xtab()`	Summary of contingency tables as HTML table
`tab_df()` `tab_dfs()`	Print data frames as HTML table.
`tab_model()`	Print regression models to HTML table
`view_df()`	View structure of labelled data frames

Reference

All functions

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