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 function

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_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

`%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

scale_mod()

Scale variables in fitted regression models

set_summ_defaults()

Set defaults for summ function

standardize()

Standardize vectors, data frames, and survey designs

`%not%` x `%just%` x `%not%<-`(<default>) `%not%<-`(<data.frame>) `%not%<-`(<matrix>) `%just%<-`(<default>) `%just%<-`(<data.frame>) `%just%<-`(<matrix>)

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