News

sjPlot 2.6.3

General

• Export dplyr::n(), to meet changes in dplyr 0.8.0.
• plot_model() and tab_model() now support MixMod-objects from package GLMMadpative, mlogit- and gmnl-models.

Renamed functions

• sjp.kfold_cv() was renamed to plot_kfold_cv().
• sjp.frq() was renamed to plot_frq().

Changes to functions

tab_model()

• tab_model() gets a show.ngrps-argument, which adds back the functionality to print the number of random effects groups for mixed models.
• tab_model() gets a show.loglik-argument, which adds back the functionality to print the model's log-Likelihood.
• tab_model() gets a strings-argument, as convenient shortcut for setting column-header strings.
• tab_model() gets additional arguments vcov.fun, vcov.type and vcov.args that are passed down to sjstats::robust(), to calculate different types of (clustered) robust standard errors.
• The p.style-argument now also allows printing both numeric p-values and asterisks, by using p.style = "both".

plot_likert()

• plot_likert() gets a reverse.scale argument to reverse the order of categories, so positive and negative values switch position.
• plot_likert() gets a groups argument, to group items in the plot (thanks to @ndevln).
• Argument grid.range in plot_likert() now may also be a vector of length 2, to define diffent length for the left and right x-axis scales.

Other

• plot_frq() (former sjp.frq()) now has pipe-consistent syntax, enables plotting multiple variables in one function call and supports grouped data frames.
• plot_model() gets additional arguments vcov.fun, vcov.type and vcov.args that are passed down to sjstats::robust(), to calculate different types of (clustered) robust standard errors.
• sjt.xtab(), sjp.xtab(), plot_frq() and sjp.grpfrq() get a drop.empty()-argument, to drop values / factor levels with no observations from output.

Bug fixes

• Legend labels were inverted for brms-models in plot_model(..., type = "diag").
• Legend labels were duplicated for marginal effects plots when color ="bw" and legend.title was specified.
• Fixed encoding issues with help-files.
• view_df() did not truncate frequency- and percentage-values for variables where value labels were truncated to a certain maximum number.
• tab_model() did not print number of observations for coxph-models.

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 2.4.1

General

• Remove unnecessary imports.
• Add back save_plot() function.
• Revised and updated package vignettes.

New functions

• tab_df() and tab_dfs() as (more generic) replacement for sjt.df(). tab_df() prints the content of a data frame as HTML table, while tab_dfs() prints a list of data frames into a HTML table. The HTML table is then displayed in the Viewer-pane of RStudio or in a web browser.

Deprecated

• sjt.grpmean() is now deprecated. Please use sjstats::grpmean() with argument out = "viewer" instead.
• sjt.mwu() is now deprecated. Please use sjstats::mwu() with argument out = "viewer" instead.
• sjt.df() is now deprecated. Please use sjmisc::descr() with argument out = "viewer" or tab_df() instead.

Changes to functions

• plot_model() now also supports clm-models from package ordinal, polr-models from package MASS, multinom-models from package nnet and Zelig-relogit-models from package Zelig.
• plot_model() gets a show.legend-argument to show or hide the legend for marginal effects plots.
• plot_model() gets a se-argument to plot (robust) standard errors instead of confidence intervals for coefficient-plots.
• Diagnostic plots in plot_model() (type = "diag") now also plot diagnostics of random effects from (generalized) linear mixed models.
• The ...-argument of plot_model() now also accepts the arguments sep_in and sep_out, which are passed down to snakecase::to_any_case() for case conversion of term labels (axis labels).
• The title-argument in plot_model() now also works for plotting random effects (type = "re").
• sjt.itemanalysis() no longer returns a list of score items, but only a data frame of scores.
• sjp.grpfrq() gets a show.ci-argument to add notches to boxplots.

Bug fixes

• view_df() did not work with double values (with decimal points) when show.values = TRUE.
• view_df() caused an error when a variable has completely missing values.
• plot_models() did not properly remove intercepts from output for survey models, when show.intercept = FALSE.
• plot_models() did not automatically transform axis for all applicable model types.
• get_model_data() did not work for marginal effects plots.
• Fixed a bug that was introduced during the past update in sjt.grpmean(), resulting in multiple table outputs and a wrong overall p-value in the summary line.
• Model weights are now correctly taken into account for marginal effect plots in plot_model().
• sjp.likert() did not show correct order for factors with character levels, when a neutral category was specified and was not the last factor level.
• Fixed issue when plotting random effects (type = "re") for specific brms-models.

sjPlot 2.4.0

General

• The old set_theme() was removed. Instead, there are some new predifined themes available (see ?"sjPlot-themes"). The former sjp.setThemes() was renamed to set_theme() instead.

New functions

• plot_model() as replacement for sjp.lm(), sjp.glm(), sjp.lmer(), sjp.glmer() and sjp.int() (which will become deprecated in the future, and will later be removed).
• get_model_data() to get the data from plot-objects created with plot_model().
• font_size(), label_angle() and legend_style() as convenient ways to tweak common ggplot-theme-elements.

Changes to functions

• view_df() now better handles string variables and gets a show.string.values-argument to omit the output of values from string variables.
• view_df() gets a max.len-argument to truncate output for variables with many values.
• view_df() displays more information on non-labelled, numeric variables.
• sjp.pca() and sjt.pca() now give more informative error messages when just one component is extracted.

Bug fixes

• Fixed bug with rm.terms-argument in plot_models().
• In rare situations, view_df() did not work for string variables with missing values.
• Fixed issue with wrong footnote text when saving the output of sjt.pca() as file.
• sjp.xtab() did not work when show.n and show.prc were set to FALSE, but show.values was TRUE.

sjPlot 2.3.3

General

• Fixed issue with latest tidyr-update on CRAN.
• HTML-tables (sjt.*-functions) displayed in the viewer pane now automatically add a CSS-style for white page background. This fixes an RStudio issue on OS X, where the new look'n'feel used dark backgrounds in the viewer pane, making output hardly readable.

sjPlot 2.3.2

General

• Revising package code from scratch. Part of the old functions will be replaced by new ones, making the code base easier to maintain and reduce redundant functions by merging them together. In the course of the next updates, functions will first become deprecated and later defunct.
• Changed imports to avoid using deprecated functions.
• Use more informative warning- and error-messages for certain functions.

New functions

• plot_models() as replacement for sjp.lmm() and sjp.glmm() (which are now deprecated).
• sjp.fa() and sjt.fa() to plot or print as table the results of factor analyses.

Bug fixes

• The mean and standard deviation in the summary of sjt.frq() were not correctly computed, when auto.group-argument was specified. This bug was introduced in the last update and is not fixed again.
• Values of character vectors were not always correctly sorted in view_df() (if show.frq = TRUE).

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 2.3.0

General

• Vignettes were added to this package.

Changes to functions

• You can use geom.colors = "bw" for linetype-plots, to create black & white figures that use different linetypes instead of different colors.
• sjp.kfold_cv() now also supports poisson and negative binomial regression models.
• sjp.pca() and sjt.pca() get a rotation-argument, to use either varimax- or oblimin-transformation of factor loadings.
• Argument show.value now also applies to bar plots in sjp.pca().
• sjt.glm(), for generalized linar (mixed) models, now shows adjusted standard errors, using the Taylor series-based delta method.
• More precise rounding of percentage values in sjt.xtab(), sjp.xtab() and sjp.grpfrq().
• Cramer's V in sjt.xtab() is now dentoted as V.
• sjt.xtab() gets a ...-argument, to pass down further arguments to the test statistics functions chisq.test() and fisher.test().
• sjt.xtab() gets a statistics-argument, to select one of different measures of associations for the table summary.

Bug fixes

• Plotting or table output of regression models did not work with null-models (i.e. with intercept only).

Reference manual