Get regression table

Output regression table for an lm() regression in "tidy" format. This function is a wrapper function for broom::tidy() and includes confidence intervals in the output table by default.

get_regression_table(
  model,
  conf.level = 0.95,
  digits = 3,
  print = FALSE,
  default_categorical_levels = FALSE
)

Arguments

model

an lm() model object

conf.level

The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.

digits

number of digits precision in output table

print

If TRUE, return in print format suitable for R Markdown

default_categorical_levels

If TRUE, do not change the non-baseline categorical variables in the term column. Otherwise non-baseline categorical variables will be displayed in the format "categorical_variable_name: level_name"

Value

A tibble-formatted regression table along with lower and upper end points of all confidence intervals for all parameters lower_ci and upper_ci; the confidence levels default to 95\

See also

tidy(), get_regression_points(), get_regression_summaries()

Examples

library(moderndive)

# Fit lm() regression:
mpg_model <- lm(mpg ~ cyl, data = mtcars)

# Get regression table:
get_regression_table(mpg_model)
#> # A tibble: 2 × 7
#>   term      estimate std_error statistic p_value lower_ci upper_ci
#>   <chr>        <dbl>     <dbl>     <dbl>   <dbl>    <dbl>    <dbl>
#> 1 intercept    37.9      2.07      18.3        0    33.6     42.1 
#> 2 cyl          -2.88     0.322     -8.92       0    -3.53    -2.22

# Vary confidence level of confidence intervals
get_regression_table(mpg_model, conf.level = 0.99)
#> # A tibble: 2 × 7
#>   term      estimate std_error statistic p_value lower_ci upper_ci
#>   <chr>        <dbl>     <dbl>     <dbl>   <dbl>    <dbl>    <dbl>
#> 1 intercept    37.9      2.07      18.3        0    32.2     43.6 
#> 2 cyl          -2.88     0.322     -8.92       0    -3.76    -1.99