如何在R中循环观察?

Question

我有以下数据框，代表受试者的ID、随访前的月数和受试者的年龄。

df1<-structure(list(USUBJID = c(1, 2, 3), 
follow_up = c(24,36,56), 
AGE = c(65,34,65)), 
row.names = c(NA, -3L), 
class = c("tbl_df", "tbl", "data.frame"))

# A tibble: 3 x 3
USUBJID follow_up   AGE
<dbl>     <dbl> <dbl>
1       1        24    65
2       2        36    34
3       3        56    65

对于每个主题，我需要根据随访列的值创建年度条目(例如，如果随访为36个月，我需要0、12、24和36个月的条目)。对于每个条目，我还需要计算受试者的年龄，并将其与原始年龄列的值相加。

这是我期望的输出:

# A tibble: 12 x 3
USUBJID Month   AGE
<dbl> <dbl> <dbl>
1       1     0    65
2       1    12    66
3       1    24    67
4       2     0    34
5       2    12    35
6       2    24    36
7       2    36    37
8       3     0    65
9       3    12    66
10       3    24    67
11       3    36    68
12       3    48    69

Answer 1

条件不是很清楚。这可能会有所帮助-根据'follow_up'列中的值复制行(uncount从tidyr)，按'USUBJID'分组，创建从0开始递增12的seq序列和递增1的'AGE'(使用row_number作为序列)

library(dplyr)
library(tidyr)
df2 <- df1 %>% 
uncount(follow_up %/% 12 + 1) %>% 
group_by(USUBJID) %>%
mutate(follow_up = seq(0, length.out = n(), by = 12), 
AGE = first(AGE) + row_number() - 1) %>% 
ungroup %>%
rename(Month = follow_up)

与产出

df2
# A tibble: 12 × 3
USUBJID     Month   AGE
<int>     <dbl> <dbl>
1       1         0    65
2       1        12    66
3       1        24    67
4       2         0    34
5       2        12    35
6       2        24    36
7       2        36    37
8       3         0    65
9       3        12    66
10       3        24    67
11       3        36    68
12       3        48    69

---

或者使用data.table

library(data.table)
setDT(df1)[rep(seq_len(.N), follow_up %/% 12 + 1)][,
.(Month = seq(0, length.out = .N, by = 12), 
AGE = first(AGE) + seq_len(.N) - 1), .(USUBJID)]

与产出

USUBJID Month   AGE
<num> <num> <num>
1:       1     0    65
2:       1    12    66
3:       1    24    67
4:       2     0    34
5:       2    12    35
6:       2    24    36
7:       2    36    37
8:       3     0    65
9:       3    12    66
10:       3    24    67
11:       3    36    68
12:       3    48    69

数据

df1 <- structure(list(USUBJID = 1:3, follow_up = c(24, 36, 56), AGE = c(65, 
34, 65)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-3L))