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sjPlot (version 2.0.0)

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. This package supports labelled data.

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Install

install.packages('sjPlot')

Monthly Downloads

20,068

Version

2.0.0

License

GPL-3

Issues

220

Pull Requests

2

Stars

606

Forks

91

Maintainer

Daniel Lüdecke

Last Published

May 18th, 2016

Functions in sjPlot (2.0.0)

dist_chisq

Plot chi-squared distributions
dist_norm

Plot normal distributions
sjc.dend

Compute hierarchical cluster analysis and visualize group classification
sjc.grpdisc

Compute a linear discriminant analysis on classified cluster groups
sjt.mwu

Summary of Mann-Whitney-Test as HTML table
sjc.elbow

Compute elbow values of a k-means cluster analysis
sjp.chi2

Plot Pearson's Chi2-Test of multiple contingency tables
sjc.kgap

Compute gap statistics for k-means-cluster
sjt.stackfrq

Summary of stacked frequencies as HTML table
sjp.setTheme

Set global theme options for sjp-functions
sjp.glm

Plot estimates, predictions or effects of generalized linear models
sjp.grpfrq

Plot grouped or stacked frequencies
sjPlot-package

Data Visualization for Statistics in Social Science
save_plot

Save ggplot-figure for print publication
sjt.pca

Summary of principal component analysis as HTML table
sjp.int

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

Plot likert scales as centered stacked bars
sjp.stackfrq

Plot stacked proportional bars
view_df

View structure of labelled data frames
sjp.glmm

Plot estimates of multiple fitted glm(er)'s
sjt.corr

Summary of correlations as HTML table
sjp.corr

Plot correlation matrix
sjp.gpt

Plot grouped proportional tables
sjp.aov1

Plot One-Way-Anova tables
sjp.poly

Plot polynomials for (generalized) linear regression
sjp.frq

Plot frequencies of variables
sjt.xtab

Summary of contingency tables as HTML table
sjc.cluster

Compute hierarchical or kmeans cluster analysis
sjp.lmer

Plot estimates, predictions or effects of linear mixed effects models
sjt.glmer

Summary of generalized linear mixed models as HTML table
sjp.lm

Plot estimates, predictions or effects of linear models
sjp.glmer

Plot estimates, predictions or effects of generalized linear mixed effects models
sjt.lm

Summary of linear regression as HTML table
dist_f

Plot F distributions
sjt.frq

Summary of frequencies as HTML table
sjt.glm

Summary of generalized linear models as HTML table
sjt.lmer

Summary of linear mixed effects models as HTML table
sjt.grpmean

Summary of grouped means as HTML table
adjust_plot_range

Adjust y range of ggplot-objects
dist_t

Plot t-distributions
sjc.qclus

Compute quick cluster analysis
sjt.df

Show (description of) data frame as HTML table
sjp.pca

Plot PCA results
sjp.xtab

Plot contingency tables
sjp.scatter

Plot (grouped) scatter plots
sjp.lmm

Plot estimates of multiple fitted lm(er)'s
sjt.itemanalysis

Summary of item analysis of an item scale as HTML table