Function reference • jtools

Summarizing and visualizing regression models
`summ()` `j_summ()`	Regression summaries with options
`summ(<lm>)`	Linear regression summaries with options
`summ(<glm>)`	Generalized linear regression summaries with options
`summ(<svyglm>)`	Complex survey regression summaries with options
`summ(<merMod>)`	Mixed effects regression summaries with options
`summ(<rq>)`	Quantile regression summaries with options
`set_summ_defaults()`	Set defaults for `summ()` functions
`export_summs()`	Export regression summaries to tables
`plot_summs()` `plot_coefs()`	Plot Regression Summaries
`effect_plot()`	Plot simple effects in regression models
Plotting and generating model predictions
`effect_plot()`	Plot simple effects in regression models
`make_predictions()`	Generate predicted data for plotting results of regression models
`make_new_data()`	Make new data for generating predicted data from regression models.
`partialize()`	Adjust observed data for partial residuals plots
Data centering and scaling tools
`gscale()`	Scale and/or center data, including survey designs
`scale_mod()`	Scale variables in fitted regression models
`center_mod()`	Center variables in fitted regression models
`standardize()`	Standardize vectors, data frames, and survey designs
`center()`	Mean-center vectors, data frames, and survey designs
Survey data tools
`svycor()`	Calculate Pearson correlations with complex survey data
`svysd()`	Calculate standard deviations with complex survey data
`weights_tests()`	Test whether sampling weights are needed
`wgttest()`	Test whether sampling weights are needed
`pf_sv_test()`	Test whether sampling weights are needed
Theming
`theme_apa()`	Format ggplot2 figures in APA style
`theme_nice()`	A nice, flexible `ggplot2` theme
`add_gridlines()` `add_x_gridlines()` `add_y_gridlines()` `drop_gridlines()` `drop_x_gridlines()` `drop_y_gridlines()`	Add and remove gridlines
`jtools_colors`	Color palettes in `jtools` functions
Miscellaneous
`center()`	Mean-center vectors, data frames, and survey designs
`center_mod()`	Center variables in fitted regression models
`effect_plot()`	Plot simple effects in regression models
`export_summs()`	Export regression summaries to tables
`get_colors()`	Get colors for plotting functions
`get_formula()`	Retrieve formulas from model objects This function is primarily an internal helper function in `jtools` and related packages to standardize the different types of formula objects used by different types of models.
`get_robust_se()`	Calculate robust standard errors and produce coefficient tables
`tidy(<summ>)` `glance(<summ.lm>)` `glance(<summ.glm>)` `glance(<summ.svyglm>)` `glance(<summ.merMod>)` `glance(<summ.rq>)`	Broom extensions for summ objects
`add_gridlines()` `add_x_gridlines()` `add_y_gridlines()` `drop_gridlines()` `drop_x_gridlines()` `drop_y_gridlines()`	Add and remove gridlines
`gscale()`	Scale and/or center data, including survey designs
`interact_plot()` `cat_plot()` `sim_slopes()` `johnson_neyman()` `probe_interaction()`	Deprecated interaction functions
`jtools_colors`	Color palettes in `jtools` functions
`knit_print.summ.lm()` `knit_print.summ.glm()` `knit_print.summ.svyglm()` `knit_print.summ.merMod()` `knit_print.summ.rq()`	knitr methods for summ
`make_new_data()`	Make new data for generating predicted data from regression models.
`make_predictions()`	Generate predicted data for plotting results of regression models
`md_table()`	Print attractive data frames in the console
`get_offset_name()` `get_weights()` `get_data()` `get_response_name()`	Utility functions for generating model predictions
`movies`	Data about movies
`%nin%`	Not `%in%`
`num_print()`	Numbering printing with signed zeroes and trailing zeroes
`partialize()`	Adjust observed data for partial residuals plots
`pf_sv_test()`	Test whether sampling weights are needed
`plot_summs()` `plot_coefs()`	Plot Regression Summaries
`predict_merMod()`	Alternative interface for `merMod` predictions
`scale_mod()`	Scale variables in fitted regression models
`set_summ_defaults()`	Set defaults for `summ()` functions
`standardize()`	Standardize vectors, data frames, and survey designs
`%not%` `%not%<-`() `%just%` `%just%<-`()	Subsetting operators
`summ(<glm>)`	Generalized linear regression summaries with options
`summ(<lm>)`	Linear regression summaries with options
`summ(<merMod>)`	Mixed effects regression summaries with options
`summ()` `j_summ()`	Regression summaries with options
`summ(<rq>)`	Quantile regression summaries with options
`summ(<svyglm>)`	Complex survey regression summaries with options
`svycor()`	Calculate Pearson correlations with complex survey data
`svysd()`	Calculate standard deviations with complex survey data
`theme_apa()`	Format ggplot2 figures in APA style
`theme_nice()`	A nice, flexible `ggplot2` theme
`weights_tests()`	Test whether sampling weights are needed
`wgttest()`	Test whether sampling weights are needed
`wrap_str()` `cat_wrap()` `warn_wrap()` `stop_wrap()` `msg_wrap()`	`cat`, `message`, `warning`, and `stop` wrapped to fit the console's width.
`wtd.sd()`	Weighted standard deviation calculation

Reference

Summarizing and visualizing regression models

Plotting and generating model predictions

Data centering and scaling tools

Survey data tools

Theming

Miscellaneous