Learn R Programming
⚠️There's a newer version (2.8.17) of this package.Take me there.

sjPlot (version 1.8.3)

Data Visualization for Statistics in Social Science

Description

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 regression models (including interaction terms) and much more.

Copy Link

Version

Install

install.packages('sjPlot')

Monthly Downloads

34,677

Version

1.8.3

License

GPL-3

Issues

230

Pull Requests

2

Stars

623

Forks

94

Maintainer

Daniel Lüdecke

Last Published

August 26th, 2015

Functions in sjPlot (1.8.3)

sjt.grpmean

Summary of grouped means as HTML table
sjc.dend

Compute hierarchical cluster analysis and visualize group classification
adjust_plot_range

Adjust y range of ggplot-objects
sjc.kgap

Compute gap statistics for k-means-cluster
dist_t

Plot t-distributions
save_plot

Save ggplot-figure for print publication
dist_f

Plot F distributions
sjp.aov1

Plot One-Way-Anova tables
sjt.corr

Summary of correlations as HTML table
sjc.cluster

Compute hierarchical or kmeans cluster analysis
sjt.xtab

Summary of contingency tables as HTML table
sjt.itemanalysis

Summary of item analysis of an item scale as HTML table
sjp.lmm

Plot coefficients of multiple fitted lm's
sjp.lm

Plot estimates or predicted values of linear models
sjp.scatter

Plot (grouped) scatter plots
sjPlot-package

Data Visualization for Statistics in Social Science
sjc.qclus

Compute quick cluster analysis
sjp.chi2

Plot Pearson's Chi2-Test of multiple contingency tables
sjp.grpfrq

Plot grouped or stacked frequencies
sjp.int

Plot interaction effects of (generalized) linear (mixed) models
sjp.glmm

Plot odds ratios (forest plots) of multiple fitted glm's
dist_chisq

Plot chi-squared distributions
sjp.corr

Plot correlation matrix
sjp.gpt

Plot grouped proportional tables
sjp.setTheme

Set global theme options for sjp-functions
dist_norm

Plot normal distributions
sjp.poly

Plot polynomials for (generalized) linear regression
sjt.glmer

Summary of generalized linear mixed models as HTML table
sjt.lmer

Summary of linear mixed effects models as HTML table
sjc.elbow

Compute elbow values of a k-means cluster analysis
sjp.glm

Plot odds ratios or predicted probabilities of generalized linear models
sjp.likert

Plot likert scales as centered stacked bars
sjp.stackfrq

Plot stacked proportional bars
view_spss

View structure of labelled data frames
sjt.lm

Summary of linear regression as HTML table
sjp.xtab

Plot contingency tables
sjt.df

Show (description of) data frame as HTML table
sjt.mwu

Summary of Mann-Whitney-Test as HTML table
sjt.pca

Summary of principal component analysis as HTML table
sjp.pca

Plot PCA results
sjp.frq

Plot frequencies of (count) variables
sjp.glmer

Plot odds ratios or predicted probabilities of generalized linear mixed effects models
sjt.stackfrq

Summary of stacked frequencies as HTML table
sjc.grpdisc

Compute a linear discriminant analysis on classified cluster groups
sjp.lmer

Plot estimates or predicted values of linear mixed effects models
sjt.frq

Summary of frequencies as HTML table
sjt.glm

Summary of generalized linear models as HTML table