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.
|Author||Daniel Lüdecke <firstname.lastname@example.org>|
|Date of publication||2017-01-10 15:32:36|
|Maintainer||Daniel Lüdecke <email@example.com>|
dist_chisq: Plot chi-squared distributions
dist_f: Plot F distributions
dist_norm: Plot normal distributions
dist_t: Plot t-distributions
plot_grid: Arrange list of plots as grid
save_plot: Save ggplot-figure for print publication
set_theme: Set default theme for sjp-functions
sjc.cluster: Compute hierarchical or kmeans cluster analysis
sjc.dend: Compute hierarchical cluster analysis and visualize group...
sjc.elbow: Compute elbow values of a k-means cluster analysis
sjc.grpdisc: Compute a linear discriminant analysis on classified cluster...
sjc.kgap: Compute gap statistics for k-means-cluster
sjc.qclus: Compute quick cluster analysis
sjp.aov1: Plot One-Way-Anova tables
sjp.chi2: Plot Pearson's Chi2-Test of multiple contingency tables
sjp.corr: Plot correlation matrix
sjp.frq: Plot frequencies of variables
sjp.glm: Plot estimates, predictions or effects of generalized linear...
sjp.glmer: Plot estimates, predictions or effects of generalized linear...
sjp.glmm: Plot estimates of multiple fitted glm(er)'s
sjp.gpt: Plot grouped proportional tables
sjp.grpfrq: Plot grouped or stacked frequencies
sjp.int: Plot interaction effects of (generalized) linear (mixed)...
sjp.kfold_cv: Plot model fit from k-fold cross-validation
sjp.likert: Plot likert scales as centered stacked bars
sjp.lm: Plot estimates, predictions or effects of linear models
sjp.lmer: Plot estimates, predictions or effects of linear mixed...
sjp.lmm: Plot estimates of multiple fitted lm(er)'s
sjplot: Wrapper to create plots and tables within a pipe-workflow
sjPlot-package: Data Visualization for Statistics in Social Science
sjp.pca: Plot PCA results
sjp.poly: Plot polynomials for (generalized) linear regression
sjp.resid: Plot predicted values and their residuals
sjp.scatter: Plot (grouped) scatter plots
sjp.setTheme: Set global theme options for sjp-functions
sjp.stackfrq: Plot stacked proportional bars
sjp.xtab: Plot contingency tables
sjt.corr: Summary of correlations as HTML table
sjt.df: Show (description of) data frame as HTML table
sjt.frq: Summary of frequencies as HTML table
sjt.glm: Summary of generalized linear models as HTML table
sjt.glmer: Summary of generalized linear mixed models as HTML table
sjt.grpmean: Summary of grouped means as HTML table
sjt.itemanalysis: Summary of item analysis of an item scale as HTML table
sjt.lm: Summary of linear regression as HTML table
sjt.lmer: Summary of linear mixed effects models as HTML table
sjt.mwu: Summary of Mann-Whitney-Test as HTML table
sjt.pca: Summary of principal component analysis as HTML table
sjt.stackfrq: Summary of stacked frequencies as HTML table
sjt.xtab: Summary of contingency tables as HTML table
view_df: View structure of labelled data frames