Make a univariate regression table for many variables from raw data frame

table.univariate.regressions

library (gtsummary)

Univariate Regression
The tbl_uvregression() function produces a table of univariate regression models. The function is a wrapper for tbl_regression(), and as a result, accepts nearly identical function arguments. The function’s results can be modified in similar ways to tbl_regression().

trial %>%
  select(response, age, grade) %>%
  tbl_uvregression(
    method = glm,
    y = response,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    pvalue_fun = ~style_pvalue(.x, digits = 2)
  ) %>%
  add_global_p() %>%  # add global p-value 
  add_nevent() %>%    # add number of events of the outcome
  add_q() %>%         # adjusts global p-values for multiple testing
  bold_p() %>%        # bold p-values under a given threshold (default 0.05)
  bold_p(t = 0.10, q = TRUE) %>% # now bold q-values under the threshold of 0.10
  bold_labels()
#> add_global_p: Global p-values for variable(s) `add_global_p(include = c("age",
#> "grade"))` were calculated with
#>   `car::Anova(mod = x$model_obj, type = "III")`
#> add_q: Adjusting p-values with
#> `stats::p.adjust(x$table_body$p.value, method = "fdr")`