为了通过 key_cols 变量区分列表中的行，最好在其之间有一个空行，有一个例子：
library(rlistings)
adae <- ex_adae
lsting <- as_listing(
df = adae,
disp_cols = c("ARM", "AGE", "SEX", "RACE", "AEDECOD", "AESEV"),
key_cols = c("USUBJID", "AETOXGR")
)
head(lsting, 15)
然后我们有：
Unique Subject Identifier Analysis Toxicity Grade Description of Planned Arm Age Sex Race Dictionary-Derived Term Severity/Intensity
———————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
AB12345-BRA-1-id-134 2 A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
3 A: Drug X 47 M WHITE dcd B.2.1.2.1 MODERATE
A: Drug X 47 M WHITE dcd D.1.1.4.2 MODERATE
AB12345-BRA-1-id-141 1 C: Combination 35 F WHITE dcd D.2.1.5.3 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
2 C: Combination 35 F WHITE dcd A.1.1.1.2 MODERATE
3 C: Combination 35 F WHITE dcd B.2.1.2.1 MODERATE
5 C: Combination 35 F WHITE dcd D.1.1.1.1 SEVERE
AB12345-BRA-1-id-236 5 B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
AB12345-BRA-1-id-265 2 C: Combination 25 M WHITE dcd C.2.1.2.1 MODERATE
3 C: Combination 25 M WHITE dcd D.1.1.4.2 MODERATE
如果每个人之间都排成一排，那就太好了，就像：
Unique Subject Identifier Analysis Toxicity Grade Description of Planned Arm Age Sex Race Dictionary-Derived Term Severity/Intensity
———————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
AB12345-BRA-1-id-134 2 A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
3 A: Drug X 47 M WHITE dcd B.2.1.2.1 MODERATE
A: Drug X 47 M WHITE dcd D.1.1.4.2 MODERATE
AB12345-BRA-1-id-141 1 C: Combination 35 F WHITE dcd D.2.1.5.3 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
2 C: Combination 35 F WHITE dcd A.1.1.1.2 MODERATE
3 C: Combination 35 F WHITE dcd B.2.1.2.1 MODERATE
5 C: Combination 35 F WHITE dcd D.1.1.1.1 SEVERE
AB12345-BRA-1-id-236 5 B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
AB12345-BRA-1-id-265 2 C: Combination 25 M WHITE dcd C.2.1.2.1 MODERATE
3 C: Combination 25 M WHITE dcd D.1.1.4.2 MODERATE
感谢您对此进行调查！
一种巧妙的方法是在列出之前操作数据，方法是将所有列转换为字符，按
USUBJIDlibrary(dplyr)
adae <- ex_adae %>%
mutate(across(everything(), as.character))
lsting <- as_listing(
df = do.call(rbind, lapply(split(adae, ~USUBJID), \(x) {
y <- setNames(data.frame(matrix(rep("", ncol(adae)), nr=1)), names(adae))
y$USUBJID <- unique(x$USUBJID)
bind_rows(x, y)
})),
disp_cols = c("ARM", "AGE", "SEX"),
key_cols = c("USUBJID", "AETOXGR")
)
head(lsting, 15)
USUBJID AETOXGR ARM AGE SEX RACE AEDECOD AESEV
——————————————————————————————————————————————————————————————————————————————————————————————————————————————————
AB12345-BRA-1-id-134
2 A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
A: Drug X 47 M WHITE dcd A.1.1.1.2 MODERATE
3 A: Drug X 47 M WHITE dcd B.2.1.2.1 MODERATE
A: Drug X 47 M WHITE dcd D.1.1.4.2 MODERATE
AB12345-BRA-1-id-141
1 C: Combination 35 F WHITE dcd D.2.1.5.3 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
C: Combination 35 F WHITE dcd A.1.1.1.1 MILD
2 C: Combination 35 F WHITE dcd A.1.1.1.2 MODERATE
3 C: Combination 35 F WHITE dcd B.2.1.2.1 MODERATE
5 C: Combination 35 F WHITE dcd D.1.1.1.1 SEVERE
AB12345-BRA-1-id-236
5 B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
B: Placebo 32 M BLACK OR AFRICAN AMERICAN dcd B.1.1.1.1 SEVERE
请注意，首先显示空白行。