sjPlot - Data Visualization for Statistics in Social Science
Following functions are now defunct:
sjt.lm(), sjt.glm(), sjt.lmer() and sjt.glmer(). Please use tab_model() instead.tab_model() supports printing simplex parameters of monotonic effects of brms models.tab_model() gets a prefix.labels-argument to add a prefix to the labels of categorical terms.rotation-argument in sjt.pca() and sjp.pca() now supports all rotations from psych::principal().plot_model() no longer automatically changes the plot-type to "slope" for models with only one predictor that is categorical and has more than two levels.type = "eff" and type = "pred" in plot_model() did not work when terms was not specified.tab_model(), the confidence intervals and p-values are now re-calculated and adjusted based on the robust standard errors.colors = "bw" was not recognized correctly for plot_model(..., type = "int").sjp.frq() with correct axis labels for non-labelled character vectors.sjt.lm(), sjt.glm(), sjt.lmer() and sjt.glmer() are now deprecated. Please use tab_model() instead.dot.size and line.size in plot_model() now also apply to marginal effects and diagnostic plots.plot_model() now uses a free x-axis scale in facets for models with zero-inflated part.plot_model() now shows multiple plots for models with zero-inflated parts when grids = FALSE.tab_model() gets a p.style and p.threshold argument to indicate significance levels as asteriks, and to determine the threshold for which an estimate is considered as significant.plot_model() and plot_models() get a p.threshold argument to determine the threshold for which an estimate is considered as significant.plot_likert().tab_model() now also accepts multiple model-objects stored in a list as argument, as stated in the help-file.file-argument now works again in sjt.itemanalysis().show.ci in tab_model() did not compute confidence intervals for different levels.sjp.scatter() was revised and renamed to plot_scatter(). plot_scatter() is pipe-friendly, and also works on grouped data frames.sjp.gpt() was revised and renamed to plot_gpt(). plot_gpt() is pipe-friendly, and also works on grouped data frames.sjp.scatter() was renamed to plot_scatter().sjp.likert() was renamed to plot_likert().sjp.gpt() was renamed to plot_gpt().sjp.resid() was renamed to plot_residuals().brmsfit-objects with categorical-family for plot_model() and tab_model().tab_model() gets a show.adj.icc-argument, to also show the adjusted ICC for mixed models.tab_model() gets a col.order-argument, reorder the table columns.hide.progress in view_df() is deprecated. Please use verbose now.statistics-argument in sjt.xtab() gets a "fisher"-option, to force Fisher's Exact Test to be used.Following functions are now defunct:
sjp.lm(), sjp.glm(), sjp.lmer(), sjp.glmer() and sjp.int(). Please use plot_model() instead.sjt.frq(). Please use sjmisc::frq(out = "v") instead.lmerModLmerTest objects.show.std) in tab_model().tab_model() as replacement for sjt.lm(), sjt.glm(), sjt.lmer() and sjt.glmer(). Furthermore, tab_model() is designed to work with the same model-objects as plot_model().scale_fill_sjplot() and scale_color_sjplot(). These provide predifined colour palettes from this package.show_sjplot_pals() to show all predefined colour palettes provided by this package.sjplot_pal() to return colour values of a specific palette.Following functions are now deprecated:
sjp.lm(), sjp.glm(), sjp.lmer(), sjp.glmer() and sjp.int(). Please use plot_model() instead.sjt.frq(). Please use sjmisc::frq(out = "v") instead.Following functions are now defunct:
sjt.grpmean(), sjt.mwu() and sjt.df(). The replacements are sjstats::grpmean(), sjstats::mwu() and tab_df() resp. tab_dfs().plot_model() and plot_models() get a prefix.labels-argument, to prefix automatically retrieved term labels with either the related variable name or label.plot_model() gets a show.zeroinf-argument to show or hide the zero-inflation-part of models in the plot.plot_model() gets a jitter-argument to add some random variation to data points for those plot types that accept show.data = TRUE.plot_model() gets a legend.title-argument to define the legend title for plots that display a legend.plot_model() now passes more arguments in ... down to ggeffects::plot() for marginal effects plots.plot_model() now plots the zero-inflated part of the model for brmsfit-objects.plot_model() now plots multivariate response models, i.e. models with multiple outcomes.plot_model() (type = "diag") can now also be used with brmsfit-objects.plot_model() (type = "diag") for Stan-models (brmsfit or stanreg resp. stanfit) can now be set with the axis.lim-argument.grid.breaks-argument for plot_model() and plot_models() now also takes a vector of values to directly define the grid breaks for the plot.plot_model() and plot_models() when the grid.breaks-argument is of length one.terms-argument for plot_model() now also allows the specification of a range of numeric values in square brackets for marginal effects plots, e.g. terms = "age [30:50]" or terms = "age [pretty]".terms- and rm.terms-arguments for plot_model() now also allows specification of factor levels for categorical terms. Coefficients for the indicted factor levels are kept resp. removed (see ?plot_model for details).plot_model() now supports clmm-objects (package ordinal).plot_model(type = "diag") now also shows random-effects QQ-plots for glmmTMB-models, and also plots random-effects QQ-plots for all random effects (if model has more than one random effect term).plot_model(type = "re") now supports standard errors and confidence intervals for glmmTMB-objects.glmmTMB-tidier, which may have returned wrong data for zero-inflation part of model.brms area now shown in each own facet per intercept.sjp.likert() for uneven category count when neutral category is specified.plot_model(type = "int") could not automatically select mdrt.values properly for non-integer variables.sjp.grpfrq() now correctly uses the complete space in facets when facet.grid = TRUE.sjp.grpfrq(type = "boxplot") did not correctly label the x-axis when one category had no elements in a vector.In-between-release for registering DOI.
sjt-functions can now be directly integrated into knitr-code-chunks, because sjPlot exports a knitr-print-method (see vignette("sjtbasic", "sjPlot")).sjtab() now also works within knitr-documents (see vignette("sjtbasic", "sjPlot")).save_plot().save_plot() now also supports svg-format.type = "eff"), the axis.title-argument can now be used to change the title of y-axes.sjp.lm(), sjp.glm(), sjp.lmer() and sjp.glmer(), if color palette has more values than needed, it is silently shortend to the required length.geom.colors now also applies to plot-type type = "ri.slope".sjt.corr() and sjp.corr() is now pearson.emph.p for printing tables of regression models now defaults to FALSE.sjt.frq() for variables with many missing values and labelled values that did not occur on that variable.value.labels had no effect for sjt.frq().sjt.grpmean() sometimes not worked for factors without variable labels.sjp.glm() used Odds Ratios as default title for y-axis when plotting marginal effects. Fixed, now y-axis is correctly labelled.sjt.glm() used "Odds Ratios" as default column heading for the estimates, even for poisson or other models. Now the string for column headers is selected based on the first model input of the function.type = "pred") for categorical variables on the x-axis.