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Build summary tables from lm model objects

Source: R/build_table.R
build_table.lm.Rd

Takes a linear regression model object and summarizes it into a ready to export, human-readable summary table.

Usage

# S3 method for lm
build_table(
  .object,
  ...,
  .test = c("F", "Chisq"),
  .col.test = FALSE,
  .level = 0.95,
  .stat.pct.sign = TRUE,
  .digits = 1,
  .p.digits = 4
)

Arguments

.object

An object of class lm.

...

One or more unquoted expressions separated by commas representing columns in the data.frame. May be specified using tidyselect helpers. If left empty, all terms are summarized.

.test

A character. The name of the stats::drop1 test to use with the model. Supported options include the F-Test ('F') and Chi-squared Test ('Chisq').

.col.test

A logical. Append a columns for the test and accompanying statistic used to derive the p-value.

.level

A double. The confidence level required.

.stat.pct.sign

A logical. Paste a percent symbol after all reported frequencies.

.digits

An integer. The number of digits to round numbers to.

.p.digits

An integer. The number of p-value digits to report. Note that the p-value still rounded to the number of digits specified in .digits.

Value

An object of class tbl_df (tibble) summarizing the provided object.

See also

build_table

Examples

library(dplyr)

data_mtcars <- datasets::mtcars |>
  mutate_at(vars('vs', 'am'), as.logical) |>
  mutate_at(vars('gear', 'carb', 'cyl'), as.factor)

fit <- lm(mpg ~ vs + drat + cyl, data = data_mtcars)

fit |> build_table()
#> # A tibble: 7 × 3
#>   Variable      `HR [CI]`         p       
#>   <chr>         <chr>             <chr>   
#> 1 "(Intercept)" "19.3 [4.1-34.6]" "0.0147"
#> 2 "vs"          "0 [-4.3-4.3]"    "0.9962"
#> 3 "drat"        "1.8 [-1.5-5.1]"  "0.2747"
#> 4 "cyl"         ""                ""      
#> 5 "   4"        "Reference"       ""      
#> 6 "   6"        "-6 [-10.1--2]"   "0.0051"
#> 7 "   8"        "-10 [-16.1--4]"  "0.0022"