fmt_regression: Turn a regression model object into a markdown-ready tibble.
In ddsjoberg/gtsummary-v0.1: Presentation-Ready Data Summary Tables

Description Usage Arguments Examples

This function uses broom::tidy from the broom or broom.mixed packages to perform the initial model formatting. Review the fmt_regression vignette for detailed examples.

fmt_regression(x, exponentiate = FALSE, label = NULL,
  include = names(stats::model.frame(x)), show_yesno = NULL,
  conf.level = 0.95, intercept = FALSE, beta_fun = fmt_beta,
  pvalue_fun = fmt_pvalue)

`x`	regression model object
`exponentiate`	logical argument passed directly to `tidy` function Default is `FALSE`
`label`	list of labels to write in the output. `list(age60 = "Age > 60")`
`include`	names of variables to include in output. Default is all variables.
`show_yesno`	Vector of names of categorical and factor variables that are `c("No", "Yes")`, `c("no", "yes")`, or `c("NO", "YES")` default to dichotomous printing (i.e. only Yes shown). To force both levels to be shown include the column name in `show_yesno`, e.g. `show_yesno = c("highgrade", "female")`
`conf.level`	confidence level passed directly to `tidy` function. Default is 0.95.
`intercept`	logical argument indicates whether to include the intercept in the output. Default is `FALSE`
`beta_fun`	function to round and format beta coefficients. Default is `fmt_beta`
`pvalue_fun`	function to round and format p-values. Default is `fmt_pvalue`

mod1 <- lm(hp ~ mpg + factor(cyl), mtcars)
fmt_regression(mod1)

mod2 <- glm(response ~ age + grade + stage, trial, family = binomial(link = "logit"))
fmt_regression(mod2, exponentiate = TRUE)

library(lme4)
mod_glmer <- glmer(am ~ hp + (1 | gear), mtcars, family = binomial)
fmt_regression(mod_glmer, exponentiate = TRUE)