问题

以下是翻译好的部分：

Long time browser, first time poster.
我长时间浏览者，第一次发帖。

I would like to merge multiple frequency tables created using tbl_summary(), and then stacked with tbl_stack(), with multiple tables of univariate logistic regressions created using tbl_regression(), also stacked using tbl_stack().
我想要合并使用 tbl_summary() 创建的多个频率表，然后使用 tbl_stack() 进行堆叠，还有使用 tbl_regression() 创建的多个一元逻辑回归表，也使用 tbl_stack() 进行堆叠。

I would like the columns to be (1) the (binary) dependent variable names, (2) the frequency % of the dependent variable by strata of a binary independent variable, (3) the OR from the regression, (4) and the 95% confidence interval from the regression. I would like the rows of the merged table to be labeled as the dependent variables from the regressions.
我希望列包括（1）（二进制）因变量的名称，（2）依赖变量在二进制独立变量分层中的频率%，（3）来自回归的OR，（4）以及来自回归的95%置信区间。我希望合并表格的行标记为回归中的因变量。

I have tried stacking then merging, in which case the rows are grouped from the tbl_summary stack and then the tbl_regression stack, but with staggered empty columns. I have also tried merging then stacking, in which case the rows are sequentially staggered, with one from tbl_summary followed by one from tbl_regression and so on.
我尝试过先堆叠再合并，在这种情况下，行是从 tbl_summary 堆叠开始的，然后是 tbl_regression 堆叠，但有错位的空列。我还尝试了先合并再堆叠，在这种情况下，行是依次错位的，从 tbl_summary 开始，然后是从 tbl_regression 等等。

The problem I think I'm running up against is that the variable names in the tbl_summary tables are preserved from the data set (the desired dependent variables), whereas the variable names in the tbl_regression tables are the independent variable.
我认为我遇到的问题是，tbl_summary 表中的变量名从数据集中保留下来（所需的因变量），而tbl_regression 表中的变量名是独立变量。

I am not fluent in the gt package, which I think could help me here...
我对gt包不够熟练，但我认为它可以帮助我在这里...

Any advice and/or sample code is appreciated!
感谢任何建议和/或示例代码！

Reprex below.
以下是示例代码。

library(gtsummary)
library(dplyr)
packageVersion("gtsummary")
#> '1.6.2'

ex <- trial %>%
  mutate(gradeI = case_when(grade == "I" ~ 1,
                            TRUE ~ 0),
         gradeII = case_when(grade == "II" ~ 1,
                            TRUE ~ 0),
         gradeIII = case_when(grade == "III" ~ 1,
                            TRUE ~ 0),
         agegp = case_when(age<47 ~ 0,
                            TRUE ~ 1))

t1 <- ex %>%
  select(gradeI, agegp) %>%
  tbl_summary(by = agegp)
t2 <- ex %>%
  select(gradeII, agegp) %>%
  tbl_summary(by = agegp)
t3 <- ex %>%
  select(gradeIII, agegp) %>%
  tbl_summary(by = agegp)

#glm1 <- glm(grade1 ~ agegp, family = binomial(), data = ex)
#glm2 <- glm(grade2 ~ agegp, family = binomial(), data = ex)
#glm2 <- glm(grade2 ~ agegp, family = binomial(), data = ex)

glm1 <- ex %>%
  select(gradeI, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeI,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade I by age group"))
glm2 <- ex %>%
  select(gradeII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade II by age group"))
glm3 <- ex %>%
  select(gradeIII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeIII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade II by age group"))

merge1 <- tbl_merge(tbls = list(t1, glm1),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))
merge2 <- tbl_merge(tbls = list(t2, glm2),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))
merge3 <- tbl_merge(tbls = list(t3, glm3),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))

tbl_stack(tbls = list(merge1, merge2, merge3))

library(gtsummary)
library(dplyr)
packageVersion("gtsummary")
#> '1.6.2'

ex <- trial %>%
  mutate(gradeI = case_when(grade == "I" ~ 1,
                            TRUE ~ 0),
         gradeII = case_when(grade == "II" ~ 1,
                            TRUE ~ 0),
         gradeIII = case_when(grade == "III" ~ 1,
                            TRUE ~ 0),
         agegp = case_when(age<47 ~ 0,
                            TRUE ~ 1))

t1 <- ex %>% select(gradeI, agegp) %>% tbl_summary(by = agegp)
t2 <- ex %>% select(gradeII, agegp) %>% tbl_summary(by = agegp)
t3 <- ex %>% select(gradeIII, agegp) %>% tbl_summary(by = agegp)

#glm1 <- glm(grade1 ~ agegp, family = binomial(), data = ex)
#glm2 <- glm(grade2 ~ agegp, family = binomial(), data = ex)
#glm2 <- glm(grade2 ~ agegp, family = binomial(), data = ex)

glm1 <- ex %>%
  select(gradeI, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeI,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade I by age group"))
glm2 <- ex %>%
  select(gradeII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade II by age group"))
glm3 <- ex %>%
  select(gradeIII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeIII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade II by age group"))

merge1 <- tbl_merge(tbls = list(t1, glm1),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))
merge2 <- tbl_merge(tbls = list(t2, glm2),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))
merge3 <- tbl_merge(tbls = list(t3, glm3),
          tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**"))

tbl_stack(tbls = list(merge1, merge2, merge3))

答案1

得分: 0

你需要匹配两个表格中的变量和标签。这些信息存储在表格主体中。我认为你应该只调用一次 tab_spanner，所以我已经交换了 tbl_stack 和 tbl_merge 的顺序。

我已经为您的结果使用了通用标签 "Grade X"。我猜您可以在调用 tbl_summary 时设置标签，但我直接在 table_body 中设置了标签。

library(gtsummary)
library(dplyr)

ex <- trial %>%
  mutate(gradeI = case_when(grade == "I" ~ 1,
                            TRUE ~ 0),
         gradeII = case_when(grade == "II" ~ 1,
                             TRUE ~ 0),
         gradeIII = case_when(grade == "III" ~ 1,
                              TRUE ~ 0),
         agegp = case_when(age < 47 ~ 0,
                           TRUE ~ 1))

t1 <- ex %>% select(gradeI, agegp) %>% tbl_summary(by = agegp)
t2 <- ex %>% select(gradeII, agegp) %>% tbl_summary(by = agegp)
t3 <- ex %>% select(gradeIII, agegp) %>% tbl_summary(by = agegp)

# 设置标签
t1$table_body$label <- "Grade I"
t2$table_body$label <- "Grade II"
t3$table_body$label <- "Grade III"

glm1 <- ex %>%
  select(gradeI, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeI,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade I"))
glm2 <- ex %>%
  select(gradeII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade II"))
glm3 <- ex %>%
  select(gradeIII, agegp) %>%
  tbl_uvregression(
    method = glm,
    y = gradeIII,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    label = list(agegp ~ "Grade III"))

# 匹配变量
glm1$table_body$variable <- "gradeI"
glm2$table_body$variable <- "gradeII"
glm3$table_body$variable <- "gradeIII"

tbl_merge(list(
  tbl_stack(list(t1,t2,t3)), 
  tbl_stack(list(glm1,glm2,glm3)), 
  tab_spanner = c("**肿瘤等级频率&lt;br&gt;按年龄组**", "**&lt;br&gt;单变量回归**")
))

library(gtsummary)
library(dplyr)
ex <- trial %>%
mutate(gradeI = case_when(grade == "I" ~ 1,
TRUE ~ 0),
gradeII = case_when(grade == "II" ~ 1,
TRUE ~ 0),
gradeIII = case_when(grade == "III" ~ 1,
TRUE ~ 0),
agegp = case_when(age<47 ~ 0,
TRUE ~ 1))
t1 <- ex %>% select(gradeI, agegp) %>% tbl_summary(by = agegp)
t2 <- ex %>% select(gradeII, agegp) %>% tbl_summary(by = agegp)
t3 <- ex %>% select(gradeIII, agegp) %>% tbl_summary(by = agegp)
# Set labels
t1$table_body$label <- "Grade I"
t2$table_body$label <- "Grade II"
t3$table_body$label <- "Grade III"
glm1 <- ex %>%
select(gradeI, agegp) %>%
tbl_uvregression(
method = glm,
y = gradeI,
method.args = list(family = binomial),
exponentiate = TRUE,
# label = list(agegp ~ "Grade I by age group"))
label = list(agegp ~ "Grade I"))
glm2 <- ex %>%
select(gradeII, agegp) %>%
tbl_uvregression(
method = glm,
y = gradeII,
method.args = list(family = binomial),
exponentiate = TRUE,
label = list(agegp ~ "Grade II"))
glm3 <- ex %>%
select(gradeIII, agegp) %>%
tbl_uvregression(
method = glm,
y = gradeIII,
method.args = list(family = binomial),
exponentiate = TRUE,
label = list(agegp ~ "Grade III"))
# Match variables
glm1$table_body$variable <- "gradeI"
glm2$table_body$variable <- "gradeII"
glm3$table_body$variable <- "gradeIII"
tbl_merge(list(
tbl_stack(list(t1,t2,t3)), 
tbl_stack(list(glm1,glm2,glm3))), 
tab_spanner = c("**Tumor grade frequencies<br>by age group**", "**<br>Univariate regression**")
)