sjPlot 2.6.2

General

• Revised some help-files and vignettes.

Removed / Defunct

Following functions are now defunct:

• sjt.lm(), sjt.glm(), sjt.lmer() and sjt.glmer(). Please use tab_model() instead.

Changes to functions

• 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.
• The rotation-argument in sjt.pca() and sjp.pca() now supports all rotations from psych::principal().

Bug fixes

• 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.
• If robust standard errors are requested in 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").
• Fix issue in sjp.frq() with correct axis labels for non-labelled character vectors.

sjPlot 2.6.1

General

• Removed defunct functions.

Deprecated

• sjt.lm(), sjt.glm(), sjt.lmer() and sjt.glmer() are now deprecated. Please use tab_model() instead.

Changes to functions

• Arguments 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.

Bug fixes

• Fixed bug from the last update that made value labels disappear for plot_likert().
• tab_model() now also accepts multiple model-objects stored in a list as argument, as stated in the help-file.
• The file-argument now works again in sjt.itemanalysis().
• Argument show.ci in tab_model() did not compute confidence intervals for different levels.

sjPlot 2.6.0

General

• 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.
• Reduce package dependencies.

Renamed functions

• 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().

Changes to functions

• Improved support for 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.
• Argument hide.progress in view_df() is deprecated. Please use verbose now.
• The statistics-argument in sjt.xtab() gets a "fisher"-option, to force Fisher's Exact Test to be used.

Removed / Defunct

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.

Bug fixes

• Due to changes in the broom and lmerTest packages, tidiers did no longer work for lmerModLmerTest objects.
• Fix issue with standardized coefficient (argument show.std) in tab_model().

sjPlot 2.5.0

New functions

• 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().
• New colour scales for ggplot-objects: 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.

Deprecated

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.

Removed / Defunct

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().

Changes to functions

• 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.
• Diagnostic plots in plot_model() (type = "diag") can now also be used with brmsfit-objects.
• Axis limits of diagnostic plots in plot_model() (type = "diag") for Stan-models (brmsfit or stanreg resp. stanfit) can now be set with the axis.lim-argument.
• The 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.
• Better default calculation for grid breaks in plot_model() and plot_models() when the grid.breaks-argument is of length one.
• The 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]".
• For coefficient-plots, the 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).

Bug fixes

• plot_model(type = "re") now supports standard errors and confidence intervals for glmmTMB-objects.
• Fixed typo for glmmTMB-tidier, which may have returned wrong data for zero-inflation part of model.
• Multiple random intercepts for multilevel models fitted with brms area now shown in each own facet per intercept.
• Remove unnecessary warning in 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.
• Problems with German umlauts when printing HTML tables were fixed.

sjPlot 2.4.5

In-between-release for registering DOI.

sjPlot 2.3.1

General

• All 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")).
• Updated Namespace for functions that moved from package sjstats to sjmisc.

Changes to functions

• Changed defaults for save_plot().
• save_plot() now also supports svg-format.
• For effect-plots (type = "eff"), the axis.title-argument can now be used to change the title of y-axes.
• For 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.
• When plotting mixed models, argument geom.colors now also applies to plot-type type = "ri.slope".
• Default correlation-method for sjt.corr() and sjp.corr() is now pearson.
• Argument emph.p for printing tables of regression models now defaults to FALSE.

Bug fixes

• Fixed bug in sjt.frq() for variables with many missing values and labelled values that did not occur on that variable.
• Argument value.labels had no effect for sjt.frq().
• Automatic label detection in 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.
• Solved issue with warning in prediction-plots (type = "pred") for categorical variables on the x-axis.

sjPlot 2.2.1

Changes to functions

• sjp.lm() for type = "ma" now uses subtitles in multi-line plot-titles.

Bug fixes

• Residuals in sjp.kfold_cv() had wrong leading sign (i.e. positive residuals were negative and vice versa).