sjPlot: Data Visualization for Statistics in Social Science (original) (raw)

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.

Version: 2.8.17
Depends: R (≥ 3.6)
Imports: graphics, grDevices, stats, utils, bayestestR, datawizard, dplyr, ggeffects, ggplot2 (≥ 3.2.0), knitr, insight, MASS, parameters, performance, purrr, rlang, scales, sjlabelled (≥ 1.1.2), sjmisc (≥ 2.8.2), sjstats (≥ 0.17.8), tidyr (≥ 1.0.0)
Suggests: brms, car, clubSandwich, cluster, cowplot, effects, haven, GPArotation, ggrepel, glmmTMB, gridExtra, ggridges, httr, lme4, nFactors, pscl, psych, rmarkdown, rstanarm, sandwich, splines, survey, TMB, testthat
Published: 2024-11-29
DOI: 10.32614/CRAN.package.sjPlot
Author: Daniel Lüdecke ORCID iD [aut, cre], Alexander Bartel ORCID iD [ctb], Carsten Schwemmer [ctb], Chuck Powell ORCID iD [ctb], Amir Djalovski [ctb], Johannes Titz ORCID iD [ctb]
Maintainer: Daniel Lüdecke <d.luedecke at uke.de>
BugReports: https://github.com/strengejacke/sjPlot/issues
License: GPL-3
URL: https://strengejacke.github.io/sjPlot/
NeedsCompilation: no
Citation: sjPlot citation info
Materials: README NEWS
In views: MixedModels
CRAN checks: sjPlot results

Documentation:

Reference manual: sjPlot.pdf
Vignettes: Black & White Figures for Print Journals (source, R code) Customize Plot Appearance (source, R code) Plotting Interaction Effects of Regression Models (source, R code) Plotting Likert Scales (source, R code) Plotting Marginal Effects of Regression Models (source, R code) Plotting Estimates (Fixed Effects) of Regression Models (source, R code) Item Analysis of a Scale or an Index (source, R code) Summary of Bayesian Models as HTML Table (source, R code) Summary of Mixed Models as HTML Table (source, R code) Summary of Regression Models as HTML Table (source, R code) Robust Estimation of Standard Errors (source, R code) Customizing HTML tables (source, R code)

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