Modify Regression/Descriptive Tables (labels, headers, caption, notes)

Works with objects created by this package (class "gtregression"): uni_reg(), multi_reg(), cox_reg(), surv_reg(), stratified regression outputs, descriptive_table(), and merge_tables(). No gtsummary dependency or fallback.

Usage

modify_table(
  gt_table,
  variable_labels = NULL,
  level_labels = NULL,
  header_labels = NULL,
  caption = NULL,
  bold_labels = FALSE,
  bold_levels = FALSE,
  remove_N = FALSE,
  remove_N_obs = FALSE,
  remove_abbreviations = FALSE,
  caveat = NULL
)

Arguments

gt_table

Table object produced by this package (must contain $table_display).

variable_labels

Named character vector, for example c(old_var = "New label", ...).

level_labels

Named list for factor levels: list(var1 = c(old = "New", ...), var2 = c(...)).

header_labels

Named character vector to rename visible headers, e.g. c("OR (95% CI)" = "Crude OR", "p-value" = "P"). Common aliases such as estimate, p.value, and N are also accepted.

caption

Optional caption/title.

bold_labels

Logical; bold variable (header) rows in the body.

bold_levels

Logical; bold factor level rows in the body.

remove_N

Logical; if TRUE, drops displayed N columns from univariable and stratified package tables. For stratified survival outputs, event columns are retained unless the original table was created with show_sample = "none".

remove_N_obs

Logical; if TRUE, suppresses multivariable complete-case footnote.

remove_abbreviations

Logical; if TRUE, removes the Abbreviations footnote line.

caveat

Optional extra footnote.

Value

The modified table object (same class as input).

Examples

birthwt_data <- data_birthwt |>
  dplyr::mutate(
    smoke = factor(smoke, levels = c(0, 1), labels = c("No", "Yes")),
    ht = factor(ht, levels = c(0, 1), labels = c("No", "Yes")),
    low = factor(low, levels = c(0, 1), labels = c("Normal BW", "Low BW"))
  )

tbl <- uni_reg(
  data = birthwt_data,
  outcome = "low",
  exposures = c("age", "smoke", "ht"),
  approach = "logit",
  format = "gt"
)

modify_table(
  tbl,
  variable_labels = c(age = "Maternal age", smoke = "Smoking"),
  level_labels = list(smoke = c(Yes = "Smoker")),
  header_labels = c(estimate = "Crude OR", p.value = "P"),
  caption = "Univariable regression for low birth weight"
)$table


  
Univariable regression for low birth weight

  
Characteristic
      
N
      
Crude OR
      
P
    
Maternal age
189
0.95 (0.89-1.01)
0.105
Smoking
189

No


Ref.
  Smoker


2.02 (1.08-3.78)
0.028
ht
189

No


Ref.
  Yes


3.37 (1.02-11.09)
0.046
Abbreviations: OR = Odds Ratio; CI = Confidence Interval.