У меня есть
> head(p)
studie sex n_fjernet n_sygdom
1 Group1 Male 22 1
2 Group1 Male 61 2
3 Group1 Female 50 1
4 Group1 Female 47 3
5 Group1 Female 30 1
6 Group1 Female 60 0
и
> head(u)
studie alder sex n_fjernet n_sygdom n_otte
1 Group4 59 Female 26 0 0
2 Group4 85 Male 7 1 1
3 Group4 74 Female 17 9 6
4 Group4 78 Male 13 0 0
5 Group4 41 Male 11 0 0
6 Group4 62 Male 12 0 0
Я хочу добавить u$n_otte к p для всех случаев p$studie==u$studie и p$sex==u$sex и p$n_fjernet==u$n_fjernet и p$n_sygdom==u$n_sygdom, что составляет 895 случаев в u из общего числа 1485 случаев в p. Все случаи в p, которые не совпадают и получают u$n_otte left_joined(), должны быть просто перечислены как NA
Итак, я написал
left_join(p, u %>% distinct(studie, sex, n_fjernet, n_sygdom, .keep_all = TRUE), by = "n_otte")
, который возвратил ошибку
Error: `by` can't contain join column `n_otte` which is missing from LHS
Я пробовал разные left_join() подходы, но все вернули ошибку. Что я делаю неправильно?
u <- structure(list(studie = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Group4",
"Group3"), class = "factor"), sex = structure(c(1L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L,
1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L
), .Label = c("Female", "Male"), class = "factor"), n_fjernet = c(26L,
7L, 17L, 13L, 11L, 12L, 8L, 2L, 14L, 8L, 35L, 23L, 5L, 20L, 11L,
5L, 30L, 12L, 23L, 37L, 13L, 26L, 9L, 9L, 9L, 15L, 39L, 13L,
5L, 9L, 19L, 32L, 18L, 16L, 45L, 35L, 25L, 20L, 27L, 34L, 11L,
44L, 20L, 48L, 92L, 6L, 29L, 12L, 26L, 37L, 30L, 54L, 32L, 39L,
15L, 21L, 22L, 34L, 39L, 30L, 36L, 19L, 26L, 43L, 26L, 42L, 18L,
15L, 32L, 29L, 36L, 28L, 38L, 35L, 66L, 11L, 49L, 32L, 61L, 49L,
36L, 51L, 42L, 13L, 10L, 36L, 45L, 49L, 52L, 21L, 42L, 29L, 38L,
28L, 37L, 47L, 33L, 50L, 19L, 45L, 23L, 29L, 31L, 59L, 60L, 32L,
32L, 30L, 50L, 29L, 32L, 42L, 24L, 22L, 47L, 24L, 22L, 8L, 38L,
25L, 34L, 45L, 50L, 51L, 28L, 8L, 21L, 17L, 30L, 36L, 20L, 56L,
23L, 77L, 23L, 76L, 58L, 35L, 33L, 52L, 34L, 17L, 66L, 38L, 58L,
16L, 58L, 44L, 22L, 42L, 17L, 33L, 9L, 31L, 15L, 46L, 31L, 32L,
25L, 17L, 31L, 35L, 29L, 18L, 69L, 28L, 25L, 35L, 19L, 18L, 15L,
51L, 41L, 55L, 35L, 19L, 45L, 24L, 39L, 57L, 45L, 37L, 30L, 33L,
34L, 47L, 21L, 16L, 22L, 26L, 36L, 32L, 17L, 28L, 32L, 35L, 37L,
30L, 32L, 29L, 41L, 18L, 26L, 32L, 30L, 17L, 35L, 17L, 27L, 27L,
10L, 30L, 50L, 28L, 22L, 13L, 32L, 35L, 51L, 44L, 16L, 17L, 43L,
27L, 21L, 34L, 13L, 18L, 37L, 20L, 8L, 19L, 43L, 24L, 48L, 15L,
11L, 22L, 20L, 19L, 20L, 23L, 12L, 31L, 28L, 34L, 25L, 22L, 38L,
28L, 26L, 30L, 45L, 50L, 39L, 22L, 41L, 14L, 60L, 35L, 10L, 29L,
24L, 25L, 31L, 32L, 33L, 10L, 16L, 10L, 10L, 32L, 30L, 34L, 31L,
24L, 15L, 20L, 20L, 31L, 33L, 15L, 27L, 19L, 40L, 17L, 48L, 35L,
25L, 25L, 22L, 19L, 24L, 20L, 30L, 13L, 28L, 19L, 7L, 29L, 18L,
41L, 11L, 42L, 35L, 24L, 16L, 29L, 39L, 28L, 32L, 16L, 31L, 30L,
27L, 17L, 28L, 29L, 12L, 25L, 30L, 14L, 19L, 13L, 32L, 16L, 12L,
24L, 10L, 34L, 49L, 17L, 11L, 37L, 38L, 36L, 18L, 42L, 14L, 33L,
41L, 21L, 10L, 16L, 16L, 14L, 32L, 25L, 22L, 19L, 28L, 16L, 24L,
28L, 29L, 34L, 27L, 23L, 33L, 23L, 57L, 30L, 16L, 13L, 20L, 42L,
14L, 18L, 31L, 19L, 22L, 27L, 11L, 12L, 7L, 25L, 29L, 35L, 21L,
64L, 39L, 51L, 21L, 16L, 36L, 22L, 15L, 29L, 38L, 20L, 23L, 5L,
33L, 15L, 20L, 52L, 31L, 16L, 10L, 12L, 47L, 23L, 28L, 27L, 18L,
24L, 34L, 45L, 24L, 43L, 28L, 34L, 20L, 26L, 17L, 41L, 25L, 38L,
35L, 25L, 21L, 24L, 21L, 24L, 14L, 40L, 19L, 11L, 21L, 38L, 43L,
23L, 28L, 17L, 78L, 12L, 27L, 16L, 24L, 16L, 21L, 43L, 25L, 50L,
44L, 30L, 33L, 31L, 20L, 47L, 47L, 34L, 22L, 31L, 28L, 51L, 23L,
45L, 30L, 34L, 32L, 39L, 41L, 25L, 15L, 19L, 14L, 41L, 40L, 49L,
27L, 35L, 26L, 22L, 59L, 10L, 29L, 38L, 64L, 16L, 36L, 56L, 31L,
50L, 23L, 27L, 49L, 30L, 28L, 25L, 38L, 37L, 25L, 30L, 23L, 18L,
31L, 48L, 47L, 49L), n_sygdom = c(0L, 1L, 9L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 4L, 0L, 0L, 21L, 0L, 2L,
0L, 0L, 0L, 2L, 1L, 1L, 0L, 0L, 2L, 2L, 0L, 0L, 7L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 11L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 7L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 5L, 6L, 0L, 1L,
0L, 1L, 0L, 0L, 1L, 0L, 3L, 0L, 0L, 19L, 2L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 4L, 0L, 0L, 0L, 0L, 0L, 3L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 5L, 0L, 2L, 6L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L,
0L, 16L, 1L, 6L, 0L, 2L, 5L, 0L, 0L, 0L, 0L, 3L, 0L, 2L, 3L,
4L, 0L, 1L, 0L, 0L, 0L, 4L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 4L, 0L, 9L, 0L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 0L, 2L,
2L, 3L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 5L, 1L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L,
2L, 5L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 8L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 2L, 0L, 14L, 3L, 0L, 0L, 0L, 0L, 4L, 1L, 0L, 0L, 2L, 0L,
1L, 0L, 0L, 1L, 0L, 2L, 0L, 5L, 0L, 0L, 0L, 1L, 0L, 0L, 4L, 0L,
1L, 1L, 3L, 0L, 2L, 0L, 0L, 0L, 2L, 7L, 18L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 3L, 1L, 0L, 0L, 6L, 1L, 0L, 0L, 7L, 2L,
0L, 0L, 0L, 1L, 0L, 8L, 0L, 0L, 3L, 3L, 1L, 3L, 2L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 3L, 0L, 4L, 0L, 0L,
1L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 9L, 0L, 0L,
6L, 0L, 1L, 0L, 1L, 1L, 2L, 0L, 5L, 4L, 0L, 4L, 0L, 0L, 0L, 2L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 8L, 0L, 0L, 3L,
0L, 3L, 0L, 0L, 0L, 0L, 0L, 5L, 0L, 3L, 1L, 7L, 3L, 0L, 0L, 2L,
0L, 1L, 0L, 0L, 0L, 2L, 0L, 2L, 0L, 3L, 1L, 0L, 3L, 0L, 0L, 4L,
0L, 1L, 5L, 4L, 16L, 0L, 1L, 5L, 1L, 0L, 1L, 0L, 0L, 0L, 3L,
0L, 4L, 2L, 4L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), n_otte = c(0L, 1L, 6L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 3L, 0L, 0L, 0L, 0L, 3L, 0L, 0L, 6L, 0L, 3L, 0L, 0L, 0L,
2L, 6L, 6L, 0L, 0L, 4L, 6L, 0L, 0L, 6L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 6L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 6L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 6L, 0L, 4L, 3L, 0L, 1L, 0L, 1L, 0L, 0L,
1L, 0L, 6L, 0L, 0L, 6L, 6L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 3L, 0L,
0L, 0L, 0L, 0L, 4L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 6L,
0L, 3L, 4L, 0L, 0L, 6L, 0L, 6L, 0L, 1L, 0L, 0L, 6L, 6L, 6L, 0L,
3L, 6L, 0L, 0L, 0L, 0L, 4L, 0L, 3L, 3L, 6L, 0L, 1L, 0L, 0L, 0L,
3L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 4L, 0L, 3L,
0L, 0L, 0L, 1L, 0L, 4L, 0L, 0L, 0L, 4L, 6L, 4L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 6L, 0L, 0L, 0L, 0L, 0L, 4L, 1L, 6L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 6L, 4L, 6L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 6L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 3L, 0L, 6L, 3L, 0L,
0L, 0L, 0L, 6L, 1L, 0L, 0L, 6L, 0L, 1L, 0L, 0L, 1L, 6L, 6L, 0L,
3L, 6L, 0L, 0L, 1L, 0L, 0L, 3L, 0L, 1L, 1L, 3L, 6L, 3L, 0L, 0L,
0L, 3L, 3L, 6L, 6L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 3L, 6L,
0L, 0L, 6L, 1L, 0L, 0L, 6L, 2L, 0L, 0L, 0L, 1L, 0L, 6L, 0L, 0L,
6L, 4L, 1L, 3L, 4L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 6L,
0L, 0L, 0L, 6L, 0L, 4L, 0L, 0L, 4L, 0L, 6L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 4L, 0L, 0L, 4L, 0L, 0L, 4L, 0L, 6L, 0L, 1L, 1L, 6L, 0L,
6L, 6L, 0L, 3L, 0L, 0L, 0L, 3L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 6L, 0L, 0L, 3L, 0L, 6L, 0L, 0L, 0L, 0L, 6L, 3L,
0L, 6L, 1L, 6L, 6L, 0L, 0L, 3L, 0L, 1L, 0L, 0L, 0L, 3L, 0L, 6L,
0L, 6L, 1L, 0L, 6L, 0L, 0L, 6L, 0L, 1L, 3L, 6L, 6L, 0L, 1L, 6L,
1L, 0L, 1L, 0L, 0L, 0L, 6L, 0L, 4L, 6L, 3L, 6L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA,
500L), class = "data.frame")
А
p <- structure(list(studie = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Group2",
"Group3", "Group4"), class = "factor"), sex = structure(c(2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L,
1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L,
2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L,
1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L,
2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L,
2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L,
2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L,
2L, 2L, 1L), .Label = c("Female", "Male"), class = "factor"),
n_fjernet = c(18L, 26L, 24L, 20L, 41L, 31L, 13L, 41L, 25L,
16L, 18L, 26L, 35L, 36L, 22L, 20L, 16L, 10L, 19L, 46L, 6L,
49L, 70L, 46L, 55L, 25L, 22L, 37L, 28L, 52L, 27L, 15L, 11L,
7L, 24L, 11L, 56L, 47L, 27L, 14L, 16L, 21L, 43L, 25L, 50L,
44L, 30L, 33L, 31L, 20L, 47L, 47L, 34L, 22L, 31L, 28L, 51L,
23L, 45L, 30L, 34L, 32L, 39L, 41L, 25L, 15L, 19L, 14L, 41L,
40L, 49L, 27L, 35L, 26L, 22L, 59L, 10L, 29L, 38L, 64L, 16L,
36L, 56L, 31L, 50L, 23L, 27L, 49L, 30L, 28L, 25L, 38L, 37L,
25L, 30L, 23L, 18L, 31L, 48L, 47L, 49L, 38L, 19L, 3L, 69L,
26L, 30L, 57L, 52L, 40L, 32L, 17L, 42L, 32L, 15L, 63L, 25L,
29L, 45L, 49L, 27L, 21L, 43L, 31L, 13L, 22L, 28L, 45L, 24L,
17L, 49L, 34L, 61L, 51L, 51L, 29L, 32L, 23L, 9L, 14L, 28L,
35L, 43L, 46L, 32L, 52L, 22L, 34L, 66L, 27L, 59L, 31L, 27L,
34L, 38L, 69L, 50L, 63L, 48L, 37L, 41L, 31L, 48L, 35L, 36L,
30L, 38L, 39L, 22L, 97L, 19L, 29L, 72L, 25L, 113L, 17L, 62L,
29L, 44L, 24L, 20L, 48L, 66L, 30L, 24L, 19L, 42L, 27L, 87L,
24L, 19L, 45L, 30L, 34L, 57L, 51L, 28L, 26L, 40L, 102L, 23L,
54L, 32L, 18L, 22L, 4L, 40L, 56L, 3L, 34L, 46L, 29L, 14L,
33L, 52L, 15L, 33L, 44L, 25L, 35L, 33L, 45L, 50L, 38L, 33L,
24L, 45L, 61L, 17L, 38L, 18L, 65L, 61L, 19L, 19L, 25L, 68L,
39L, 21L, 18L, 39L, 36L, 46L, 35L, 68L, 18L, 14L, 18L, 28L,
55L, 30L, 40L, 57L, 52L, 91L, 60L, 84L, 92L, 26L, 65L, 39L,
73L, 36L, 33L, 51L, 133L, 66L, 62L, 38L, 53L, 70L, 33L, 20L,
52L, 45L, 64L, 106L, 70L, 24L, 23L, 44L, 35L, 31L, 52L, 46L,
33L, 15L, 42L, 35L, 33L, 19L, 54L, 64L, 37L, 27L, 51L, 27L,
52L, 61L, 38L, 31L, 46L, 86L, 44L, 58L, 32L, 27L, 13L, 12L,
38L, 72L, 20L, 59L, 37L, 27L, 23L, 59L, 36L, 28L, 38L, 26L,
64L, 34L, 38L, 21L, 34L, 44L, 33L, 55L, 38L, 51L, 49L, 45L,
44L, 40L, 33L, 19L, 18L, 45L, 52L, 63L, 16L, 24L, 50L, 59L,
98L, 60L, 63L, 49L, 59L, 35L, 35L, 38L, 56L, 78L, 68L, 56L,
42L, 80L, 58L, 39L, 50L, 17L, 37L, 40L, 22L, 51L, 32L, 34L,
17L, 33L, 18L, 33L, 25L, 4L, 57L, 47L, 27L, 33L, 20L, 42L,
29L, 41L, 22L, 17L, 9L, 17L, 39L, 78L, 19L, 37L, 50L, 34L,
14L, 29L, 49L, 25L, 33L, 54L, 47L, 12L, 18L, 30L, 22L, 33L,
52L, 80L, 20L, 33L, 61L, 34L, 36L, 67L, 35L, 36L, 24L, 12L,
47L, 29L, 38L, 30L, 25L, 19L, 28L, 37L, 72L, 31L, 39L, 36L,
30L, 60L, 45L, 29L, 56L, 44L, 124L, 42L, 39L, 26L, 74L, 25L,
25L, 124L, 32L, 28L, 32L, 9L, 21L, 25L, 24L, 40L, 14L, 42L,
49L, 21L, 28L, 44L, 38L, 24L, 28L, 34L, 26L, 46L, 36L, 31L,
39L, 22L, 80L, 37L, 54L, 19L, 14L, 55L, 42L, 45L, 23L, 31L,
21L, 33L, 25L, 18L, 46L, 22L, 54L, 32L, 28L, 28L, 31L, 28L,
29L, 41L, 34L, 24L, 41L, 32L, 39L, 14L, 32L, 46L, 32L), n_sygdom = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 3L, 8L, 5L, 8L,
3L, 6L, 3L, 3L, 3L, 6L, 13L, 7L, 16L, 12L, 5L, 4L, 6L, 10L,
8L, 3L, 7L, 6L, 6L, 10L, 5L, 7L, 8L, 5L, 3L, 2L, 3L, 4L,
4L, 2L, 4L, 5L, 2L, 2L, 5L, 2L, 2L, 12L, 7L, 3L, 7L, 4L,
9L, 6L, 3L, 3L, 4L, 1L, 12L, 3L, 3L, 4L, 3L, 2L, 2L, 3L,
2L, 3L, 2L, 4L, 8L, 2L, 2L, 3L, 4L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 5L, 1L, 9L, 2L, 22L, 3L, 2L, 6L, 4L, 2L, 3L, 3L,
2L, 4L, 4L, 4L, 4L, 3L, 17L, 2L, 7L, 2L, 1L, 4L, 6L, 6L,
8L, 8L, 5L, 2L, 3L, 3L, 3L, 3L, 5L, 2L, 2L, 2L, 2L, 2L, 4L,
4L, 6L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L,
1L, 2L, 2L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 3L,
2L, 2L, 2L, 3L, 3L, 4L, 3L, 2L, 3L, 2L, 2L, 8L, 2L, 3L, 3L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 4L, 3L, 1L, 3L, 13L, 4L, 9L, 4L, 3L, 2L, 3L, 4L,
3L, 2L, 8L, 4L, 10L, 10L, 2L, 3L, 6L, 8L, 6L, 3L, 3L, 2L,
7L, 5L, 3L, 12L, 2L, 2L, 1L, 2L, 3L, 1L, 2L, 5L, 2L, 7L,
3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L)), row.names = c(NA,
500L), class = "data.frame")