gtsummary 中的样式回归表

Question

我想以下面的格式设置回归表的样式。 这部分有点挑战是在最后的 output 中处理 NA ...我如何删除它们？

library(gtsummary)
library(stringr)

# build logistic regression model
m1 <- glm(response ~ age + stage, trial, family = binomial(link = "logit"))

tbl_m1 <- tbl_regression(m1, exponentiate = TRUE)

# Format the output inf the form OR (conf.low, conf.high)

tbl_m1$table_body <- tbl_m1$table_body %>%
  mutate(
    estimate = round(estimate, 1),
    conf.low = round(conf.low, 1),
    conf.high = round(conf.high, 1),
    #estimate = ifelse(is.na(estimate), "", estimate),
    ci = str_glue("{estimate}", " (", "{conf.low}, {conf.high}", ")") )

tbl_m1 %>%
  modify_header(label = "**Variable**",
                          ci = "**COR**") %>%
  modify_table_styling(
    columns = c("ci")) %>%
  modify_column_hide(c(estimate, p.value))

Answer 1

这是我会怎么做！

library(gtsummary)
packageVersion("gtsummary")
#> [1] '1.6.2'

# build logistic regression model
m1 <- glm(response ~ age + stage, trial, family = binomial(link = "logit"))

tbl_regression(m1, exponentiate = TRUE, estimate_fun = \(x) style_number(x, digits = 1)) |> 
  modify_column_merge(pattern = "{estimate} ({ci})", rows = !is.na(estimate)) |> 
  modify_header(label = "**Variable**", estimate = "**COR**") |> 
  as_kable() # convert to kable to display on StackOverflow

多变的	心率	p值
年龄	1.0 (1.0, 1.0)	0.091
T台
T1	—
T2	0.6 (0.2, 1.4)	0.2
T3	0.9 (0.4, 2.3)	0.9
T4	0.8 (0.3, 1.9)	0.6

^{创建于 2022-11-23，使用reprex v2.0.2}