Skip to contents

Get regression table

Source: R/regression_functions.R
get_regression_table.Rd

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

Usage

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

Arguments

model

an lm() or glm() 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"

exponentiate

If TRUE, exponentiate the coefficient estimates and confidence intervals. Useful for glm() models with log or logit links (returns rate or odds ratios respectively). Default FALSE.

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:
life_exp_model <- lm(
  life_expectancy_2022 ~ gdp_per_capita,
  data = un_member_states_2024
)

# Get regression table:
get_regression_table(life_exp_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          71.4     0.479    149.         0     70.5     72.4
#> 2 gdp_per_capita      0       0          9.85       0      0        0  

# Vary confidence level of confidence intervals
get_regression_table(life_exp_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          71.4     0.479    149.         0     70.2     72.7
#> 2 gdp_per_capita      0       0          9.85       0      0        0