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, PCA and correlation matrices, cluster analyses, scatter plots, Likert scales, effects plots of interaction terms in regression models, constructing index or score variables and much more.

Installation

Latest development build

To install the latest development snapshot (see latest changes below), type following commands into the R console:

library(devtools)
devtools::install_github("sjPlot/devel")

Please note that the latest development snapshot most likely depends on the latest build of the sjmisc-package, so you probably want to install it as well:

devtools::install_github("sjPlot/sjmisc")

Officiale, stable release

  

To install the latest stable release from CRAN, type following command into the R console:

install.packages("sjPlot")

Documentation and examples

• Documentation and examples

Citation

In case you want / have to cite my package, please use citation('sjPlot') for citation information. Since core functionality of package depends on the ggplot-package, consider citing this package as well.

Changelog of stable release 1.8.3

New functions

• sjp.gpt to plot grouped proportional tables.
• save_plot as convenient function to save the last ggplot-figure in high quality for publication.

Changes to functions

• sjp.lmm can now also plot standardized estimates.
• sjp.lm, sjp.lmm and sjt.lm can now plot standardized estimates, where standardization is computed following Gelman's approach by dividing estimates by two standard deviations.
• sjp.lm, sjp.glm, sjp.lmm, sjp.glmm, sjp.lmer and sjp.glmer get a remove.estimates argument to remove specific estimates from the plot output.
• Added parameters ci.hyphen and minus.sign to sjt.lm, sjt.glm, sjt.lmer and sjt.glmer to set specific symbols or HTML entitities for hyphens and minus signs of negative numbers.
• Added type = "coeff" to sjp.lmer to plot joint random and fixed effects coefficients.
• type = "poly" in sjp.lm can now deal with fitted models that either use polynomials with poly or splines with bs (see examples).
• sjt.df gets a big.mark parameter to add thousands-separators if parameter describe = TRUE.
• sjt.df and view_df now recognize Date and POSIX-classes, if showType = TRUE.
• sjp.poly now also returns cutpoints of loess curvature, to get maximum / minimum values of loess curvature.
• sjp.lm with type = "ma" now also returns all plots as list of ggplot-objects.
• sjp.setTheme now allows for custom label and title colors when using pre-set-themes.
• Improved automatic y-axis-limit detection in sjp.frq and sjp.grpfrq.
• Minor improvements to sjp.lmm and sjp.glmm.

Bug fixes

• Fixed bug in sjp.lmer, which misleadingly printed wrong beta coefficients (they were exponentiated as for odds ratios).
• Fixed bug with computation of predicted probabilities in sjp.glm and sjp.glmer (only occured when type = "y.pc").
• sjp.grpfrq did not show correct number of missings (argument na.rm = FALSE), if grouping variable startet with zero.
• Fixed bug with sjp.frq and sjt.frq, when variable was a labelled factor with lowest factor level smaller than 1.
• Fixed bug in view_df with parameter showFreq = TRUE, when variable was a character vector.
• Minor bug fixes with p-shapes in sjp.lmm and sjp.glmm.
• Fixed bug in sjt-table functions that occured with invalid multibyte strings.