如何在expss中对因子变量透视且保留标签？

我需要报告多个因子变量的汇总表，希望生成节省空间的格式（无需重复每个变量的标签）。现有数据如下：

df<-
structure(list(answer3 = 
               structure(c(NA, 2L, NA, 1L, 2L), 
              levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Confident in math class", class = c("labelled", 
              "factor")), answer4 = structure(c(NA, 2L, NA, 2L, 2L), levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Strong belong scientific community", class = c("labelled", 
              "factor")), answer5 = structure(c(NA, 5L, NA, 2L, 3L), levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Think myself a scientist", class = c("labelled", 
              "factor")), answer6 = structure(c(NA, 3L, NA, 1L, 3L), levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Important to learn concepts", class = c("labelled", 
              "factor")), answer7 = structure(c(NA, 2L, NA, 3L, 2L), levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Goal learn as much as I can", class = c("labelled", 
              "factor")), answer8 = structure(c(NA, 1L, NA, 3L, 2L), levels = c("Strongly agree", 
              "Agree", "Neutral", "Disagree", "Strongly disagree"), label = "Later changes depend on doing well", class = c("labelled", 
              "factor"))), row.names = c(NA, -5L), class = c("tbl_df", "tbl", "data.frame"))

尝试过两种方法，但都有问题：

• 方法1：生成的表格会重复选项标签，浪费空间

df %>% 
 tab_cells(answer3,answer4,answer5,answer6,answer7,answer8) %>%  
 tab_rows() %>%  tab_stat_cpct() %>%  
 tab_pivot()  # 每个变量列都会重复显示"Strongly agree"等选项标签

• 方法2：转长后丢失原变量的标签，表格只能显示answer3这类变量名

df %>% 
  to_long(cols=starts_with("answ"),value_factor = T) %>% # 变量标签被清除
    tab_cells(value) %>%
    tab_cols(variable) %>%
 tab_stat_cpct() %>%
tab_pivot() %>% tab_transpose() 

请问如何实现透视操作且不丢失变量标签？

方法1：用tbl_summary直接生成紧凑汇总表 #

gtsummary的tbl_summary可以自动识别变量标签，默认生成的格式会把所有分类变量的选项合并到同一列，变量标签作为行名，完全符合节省空间的需求：

library(gtsummary)

df %>%
  tbl_summary(
    type = all_categorical() ~ "categorical",
    statistic = all_categorical() ~ "{p}%", # 指定显示百分比
    label = everything() ~ label # 直接调用原数据的变量标签
  ) %>%
  modify_spanning_header(all_categorical() ~ "**Response Options**") %>%
  modify_header(label ~ "**Question**")

方法2：转长时手动保留变量标签 #

如果一定要用to_long转长，可以先提取原数据的变量标签，再合并到转长后的数据集里：

library(gtsummary)
library(dplyr)

# 提取所有变量的标签
var_labels <- df %>%
  map_chr(~attr(.x, "label")) %>%
  tibble(variable = names(.), question_label = .)

# 转长并合并标签
df_long <- df %>%
  to_long(cols = starts_with("answ"), value_factor = TRUE) %>%
  left_join(var_labels, by = "variable") %>%
  mutate(variable = question_label) # 用标签替换原变量名

# 生成汇总表
df_long %>%
  tab_cells(value) %>%
  tab_cols(variable) %>%
  tab_stat_cpct() %>%
  tab_pivot() %>%
  tab_transpose() %>%
  modify_header(label ~ "**Question**", all_stat_cols() ~ "**{level}**")

内容的提问来源于stack exchange，提问作者Ben