Package: sjPlot 2.8.16.2

Daniel Lüdecke

sjPlot: Data Visualization for Statistics in Social Science

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.

Authors:Daniel Lüdecke [aut, cre], Alexander Bartel [ctb], Carsten Schwemmer [ctb], Chuck Powell [ctb], Amir Djalovski [ctb], Johannes Titz [ctb]

sjPlot_2.8.16.2.tar.gz
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sjPlot.pdf |sjPlot.html
sjPlot/json (API)
NEWS

# Install 'sjPlot' in R:
install.packages('sjPlot', repos = c('https://ar-puuk.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/strengejacke/sjplot/issues

Datasets:
  • efc - Sample dataset from the EUROFAMCARE project

On CRAN:

data-visualizationplottingsocial-sciencesstatistics

15.97 score 609 stars 3 packages 6.8k scripts 35k downloads 133 mentions 49 exports 49 dependencies

Last updated 3 hours agofrom:d61e1ae27e. Checks:OK: 7. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 25 2024
R-4.5-winOKNov 25 2024
R-4.5-linuxOKNov 25 2024
R-4.4-winOKNov 25 2024
R-4.4-macOKNov 25 2024
R-4.3-winOKNov 25 2024
R-4.3-macOKNov 25 2024

Exports:css_themedist_chisqdist_fdist_normdist_tfont_sizeget_model_datalabel_anglelegend_styleplot_frqplot_gptplot_gridplot_grpfrqplot_kfold_cvplot_likertplot_modelplot_modelsplot_residualsplot_scatterplot_stackfrqplot_xtabsave_plotscale_color_sjplotscale_fill_sjplotset_themeshow_sjplot_palssjp.aov1sjp.chi2sjp.corrsjp.polysjplotsjplot_palsjt.itemanalysissjt.xtabsjtabtab_corrtab_dftab_dfstab_fatab_itemscaletab_modeltab_pcatab_stackfrqtab_xtabtheme_538theme_blanktheme_sjplottheme_sjplot2view_df

Dependencies:bayestestRclicpp11datawizarddplyreffectsizeevaluatefansifarvergenericsggeffectsggplot2gluegtablehighrinsightisobandknitrlabelinglatticelifecyclemagrittrMASSMatrixmgcvnlmeparametersperformancepillarpkgconfigpurrrR6RColorBrewerrlangscalessjlabelledsjmiscsjstatsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxfunyaml

Black & White Figures for Print Journals

Rendered fromblackwhitefigures.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2021-11-23
Started: 2017-02-05

Customize Plot Appearance

Rendered fromcustplot.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2021-11-23
Started: 2017-02-03

Customizing HTML tables

Rendered fromtable_css.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2020-05-23
Started: 2018-07-09

Item Analysis of a Scale or an Index

Rendered fromsjtitemanalysis.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2020-05-23
Started: 2017-02-03

Plotting Estimates (Fixed Effects) of Regression Models

Rendered fromplot_model_estimates.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2023-03-13
Started: 2017-10-06

Plotting Interaction Effects of Regression Models

Rendered fromplot_interactions.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2023-03-13
Started: 2018-01-22

Plotting Likert Scales

Rendered fromplot_likert_scales.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2023-03-13
Started: 2019-06-26

Plotting Marginal Effects of Regression Models

Rendered fromplot_marginal_effects.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2023-08-11
Started: 2018-01-22

Robust Estimation of Standard Errors, Confidence Intervals and p-values

Rendered fromtab_model_robust.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2022-04-05
Started: 2020-05-08

Summary of Bayesian Models as HTML Table

Rendered fromtab_bayes.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2023-03-31
Started: 2018-07-09

Summary of Mixed Models as HTML Table

Rendered fromtab_mixed.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2020-01-22
Started: 2018-07-09

Summary of Regression Models as HTML Table

Rendered fromtab_model_estimates.Rmdusingknitr::rmarkdownon Nov 25 2024.

Last update: 2021-07-10
Started: 2018-07-09

Readme and manuals

Help Manual

Help pageTopics
Data Visualization for Statistics in Social SciencesjPlot-package sjPlot
Plot chi-squared distributionsdist_chisq
Plot F distributionsdist_f
Plot normal distributionsdist_norm
Plot t-distributionsdist_t
Sample dataset from the EUROFAMCARE projectefc
Plot frequencies of variablesplot_frq
Plot grouped proportional tablesplot_gpt
Arrange list of plots as gridplot_grid
Plot grouped or stacked frequenciesplot_grpfrq
Plot model fit from k-fold cross-validationplot_kfold_cv
Plot likert scales as centered stacked barsplot_likert
Plot regression modelsget_model_data plot_model
Forest plot of multiple regression modelsplot_models
Plot predicted values and their residualsplot_residuals
Plot (grouped) scatter plotsplot_scatter
Plot stacked proportional barsplot_stackfrq
Plot contingency tablesplot_xtab
Save ggplot-figure for print publicationsave_plot
Set global theme options for sjp-functionsset_theme
Plot One-Way-Anova tablessjp.aov1
Plot Pearson's Chi2-Test of multiple contingency tablessjp.chi2
Plot correlation matrixsjp.corr
Plot polynomials for (generalized) linear regressionsjp.poly
Wrapper to create plots and tables within a pipe-workflowsjplot sjtab
Modify plot appearancecss_theme font_size label_angle legend_style scale_color_sjplot scale_fill_sjplot show_sjplot_pals sjPlot-themes sjplot_pal theme_538 theme_blank theme_sjplot theme_sjplot2
Summary of correlations as HTML tabletab_corr
Print data frames as HTML table.tab_df tab_dfs
Summary of factor analysis as HTML tabletab_fa
Summary of item analysis of an item scale as HTML tablesjt.itemanalysis tab_itemscale
Print regression models as HTML tabletab_model
Summary of principal component analysis as HTML tabletab_pca
Summary of stacked frequencies as HTML tabletab_stackfrq
Summary of contingency tables as HTML tablesjt.xtab tab_xtab
View structure of labelled data framesview_df