Nothing
inst/extdata/MOf.R
In forsearch: Diagnostic Analysis Using Forward Search Procedure for Various Models
MOf <-
list(`Number of rows included in Step 1` = 12, Subgroups = structure(c(1L,
2L, 3L, 4L, 5L, 6L, 4L, 2L, 5L, 3L, 6L, 1L), .Dim = c(6L, 2L), .Dimnames = list(
NULL, c("GroupNo", "groups.df1"))), `Rows by subgroup` = list(
structure(list(Observation = c(10L, 11L, 12L, 28L, 29L, 30L,
46L, 47L, 48L), Worker = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = "4", class = c("ordered", "factor"
)), Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.100015418261215,
52.300012698995246, 50.300016992158092, 63.199992088678037,
62.80001194095987, 62.200014699437098, 64.099989662253492,
66.199988194793406, 64.000003858730594)), row.names = c("10",
"11", "12", "28", "29", "30", "46", "47", "48"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(4L, 5L, 6L, 22L, 23L, 24L, 40L, 41L,
42L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "2", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.800004190474247,
52.800017306728911, 53.100008321597805, 59.700004029165804,
59.999977345031716, 59.000014059214266, 61.499984036554615,
61.700016288997055, 62.300005712008371)), row.names = c("4",
"5", "6", "22", "23", "24", "40", "41", "42"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(13L, 14L, 15L, 31L, 32L, 33L, 49L, 50L,
51L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "5", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(50.899992783998627,
51.79999844057339, 51.399996533640731, 64.799982341634859,
64.999998350602681, 65.399983036289882, 72.100010851567291,
72.000013954776875, 71.099997050762198)), row.names = c("13",
"14", "15", "31", "32", "33", "49", "50", "51"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(7L, 8L, 9L, 25L, 26L, 27L, 43L, 44L,
45L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "3", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(60.000008840809357,
60.199994043978684, 58.400008955249142, 68.59999645732411,
65.799986207004295, 69.700003515660342, 70.8000223691228,
70.599992584344704, 71.000022149245822)), row.names = c("7",
"8", "9", "25", "26", "27", "43", "44", "45"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(16L, 17L, 18L, 34L, 35L, 36L, 52L, 53L,
54L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "6", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(46.399983462321494,
44.800011309888738, 49.199993543570386, 43.700020166121483,
44.199977256271644, 43.000015614249733, 61.999986912968772,
61.399995070498328, 60.499990762286593)), row.names = c("16",
"17", "18", "34", "35", "36", "52", "53", "54"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(1L, 2L, 3L, 19L, 20L, 21L, 37L, 38L,
39L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "1", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.9999847465496,
52.800018242965983, 53.100021313807311, 62.100010389795997,
62.600005516019962, 63.999988679272988, 67.499977199190411,
67.19999628062493, 66.900000067831414)), row.names = c("1",
"2", "3", "19", "20", "21", "37", "38", "39"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame"))), `Rows in stage` = list(
NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL,
NULL, c(8L, 19L, 20L, 28L, 29L, 30L, 40L, 41L, 42L, 52L,
53L, 54L), c(30L, 29L, 41L, 40L, 31L, 32L, 8L, 7L, 52L, 53L,
19L, 20L, 42L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L,
53L, 19L, 20L, 40L, 28L), c(30L, 29L, 42L, 41L, 31L, 32L,
8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 21L), c(30L, 29L, 42L,
41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L, 19L, 28L, 40L, 21L,
48L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L), c(29L, 30L, 42L, 41L, 31L,
32L, 8L, 7L, 52L, 53L, 20L, 19L, 28L, 40L, 21L, 48L, 46L,
54L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L), c(30L, 29L, 42L,
41L, 31L, 32L, 8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 21L,
48L, 46L, 54L, 23L, 22L), c(30L, 29L, 42L, 41L, 31L, 32L,
8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 54L, 21L, 48L, 46L,
23L, 22L, 33L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L,
53L, 20L, 19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L,
24L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 19L,
20L, 40L, 28L, 54L, 21L, 48L, 46L, 23L, 22L, 33L, 24L, 26L
), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L, 24L, 26L,
47L), c(29L, 30L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L, 26L, 24L,
47L, 9L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L,
20L, 19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L, 24L,
26L, 47L, 9L, 39L), c(29L, 30L, 42L, 41L, 31L, 32L, 8L, 7L,
52L, 53L, 20L, 19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L,
33L, 26L, 24L, 47L, 9L, 39L, 38L), c(29L, 28L, 42L, 41L,
31L, 32L, 8L, 7L, 52L, 53L, 20L, 19L, 30L, 40L, 21L, 48L,
46L, 54L, 33L, 23L, 22L, 26L, 47L, 24L, 39L, 9L, 38L, 37L
), c(29L, 28L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 30L, 21L, 48L, 46L, 40L, 54L, 33L, 23L, 26L, 22L, 47L,
24L, 39L, 38L, 9L, 37L, 25L), c(28L, 29L, 42L, 41L, 31L,
32L, 26L, 8L, 52L, 53L, 20L, 21L, 30L, 48L, 19L, 46L, 40L,
33L, 54L, 7L, 23L, 47L, 22L, 39L, 24L, 38L, 37L, 9L, 25L,
27L), c(28L, 29L, 42L, 41L, 31L, 32L, 26L, 8L, 52L, 53L,
20L, 21L, 48L, 46L, 30L, 19L, 40L, 33L, 54L, 47L, 7L, 23L,
22L, 39L, 38L, 37L, 24L, 9L, 25L, 27L, 44L), c(28L, 48L,
42L, 41L, 31L, 32L, 26L, 8L, 52L, 53L, 21L, 20L, 46L, 29L,
30L, 19L, 33L, 40L, 47L, 54L, 39L, 7L, 23L, 38L, 22L, 37L,
24L, 25L, 9L, 27L, 44L, 43L), c(48L, 46L, 42L, 41L, 31L,
32L, 26L, 8L, 52L, 53L, 21L, 20L, 28L, 29L, 30L, 33L, 19L,
40L, 47L, 39L, 54L, 38L, 37L, 7L, 23L, 22L, 24L, 25L, 9L,
27L, 44L, 43L, 45L), c(48L, 46L, 42L, 41L, 31L, 32L, 26L,
8L, 52L, 53L, 21L, 20L, 28L, 29L, 33L, 30L, 19L, 47L, 40L,
39L, 38L, 54L, 37L, 7L, 23L, 22L, 25L, 24L, 9L, 27L, 44L,
43L, 45L, 51L), c(46L, 48L, 42L, 41L, 31L, 32L, 26L, 8L,
52L, 53L, 21L, 20L, 28L, 33L, 29L, 30L, 47L, 19L, 40L, 39L,
38L, 37L, 54L, 7L, 23L, 25L, 22L, 24L, 27L, 9L, 44L, 43L,
45L, 51L, 50L), c(46L, 48L, 42L, 41L, 31L, 32L, 26L, 25L,
52L, 53L, 21L, 20L, 33L, 28L, 29L, 47L, 30L, 19L, 39L, 38L,
40L, 37L, 54L, 8L, 7L, 23L, 22L, 27L, 24L, 9L, 44L, 43L,
45L, 51L, 50L, 49L), c(46L, 48L, 42L, 41L, 31L, 32L, 26L,
25L, 52L, 53L, 21L, 20L, 33L, 28L, 47L, 29L, 39L, 30L, 19L,
38L, 37L, 40L, 54L, 8L, 7L, 23L, 22L, 27L, 24L, 44L, 43L,
9L, 45L, 51L, 50L, 49L, 3L), c(46L, 48L, 42L, 41L, 31L, 32L,
26L, 8L, 52L, 53L, 21L, 20L, 33L, 28L, 29L, 47L, 30L, 19L,
39L, 40L, 38L, 37L, 54L, 25L, 7L, 23L, 22L, 24L, 27L, 9L,
44L, 43L, 45L, 51L, 50L, 49L, 3L, 6L), c(48L, 46L, 42L, 41L,
31L, 32L, 26L, 8L, 52L, 53L, 21L, 20L, 28L, 29L, 33L, 30L,
19L, 47L, 40L, 39L, 38L, 37L, 54L, 7L, 23L, 22L, 25L, 24L,
9L, 27L, 44L, 43L, 45L, 51L, 50L, 49L, 3L, 6L, 2L), c(48L,
46L, 42L, 41L, 31L, 32L, 26L, 8L, 52L, 53L, 21L, 20L, 28L,
29L, 30L, 19L, 33L, 40L, 47L, 39L, 54L, 38L, 7L, 23L, 37L,
22L, 24L, 25L, 9L, 27L, 44L, 43L, 45L, 51L, 50L, 49L, 3L,
6L, 2L, 5L), c(28L, 48L, 42L, 41L, 31L, 32L, 26L, 8L, 52L,
53L, 21L, 20L, 46L, 29L, 30L, 19L, 33L, 40L, 47L, 54L, 39L,
7L, 23L, 38L, 22L, 37L, 24L, 9L, 25L, 27L, 44L, 43L, 45L,
51L, 50L, 49L, 3L, 6L, 2L, 5L, 11L), c(28L, 29L, 42L, 41L,
31L, 32L, 26L, 8L, 52L, 53L, 20L, 21L, 48L, 46L, 30L, 19L,
40L, 33L, 54L, 47L, 7L, 23L, 22L, 39L, 38L, 24L, 37L, 9L,
25L, 27L, 44L, 43L, 45L, 51L, 50L, 49L, 3L, 6L, 2L, 5L, 11L,
1L), c(29L, 28L, 42L, 41L, 31L, 32L, 8L, 26L, 52L, 53L, 20L,
19L, 30L, 21L, 48L, 46L, 40L, 54L, 33L, 7L, 23L, 22L, 47L,
24L, 39L, 38L, 9L, 37L, 25L, 27L, 44L, 43L, 45L, 51L, 50L,
49L, 3L, 6L, 2L, 5L, 11L, 1L, 4L), c(29L, 30L, 42L, 41L,
31L, 32L, 8L, 7L, 52L, 53L, 20L, 19L, 28L, 40L, 21L, 48L,
46L, 54L, 23L, 33L, 22L, 26L, 47L, 24L, 39L, 9L, 38L, 37L,
25L, 27L, 44L, 43L, 45L, 51L, 50L, 49L, 3L, 6L, 2L, 5L, 11L,
1L, 4L, 14L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L,
53L, 20L, 19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L,
26L, 24L, 47L, 9L, 39L, 38L, 37L, 25L, 27L, 44L, 43L, 45L,
51L, 3L, 6L, 50L, 2L, 5L, 49L, 11L, 1L, 4L, 14L, 15L), c(30L,
29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 19L, 20L, 40L,
28L, 54L, 21L, 48L, 46L, 23L, 22L, 24L, 33L, 26L, 9L, 47L,
39L, 38L, 37L, 25L, 27L, 44L, 43L, 45L, 51L, 3L, 6L, 2L,
5L, 50L, 11L, 49L, 1L, 4L, 14L, 15L, 10L), c(30L, 29L, 41L,
42L, 31L, 32L, 8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 54L,
23L, 21L, 48L, 46L, 22L, 24L, 33L, 9L, 26L, 47L, 39L, 38L,
37L, 25L, 27L, 44L, 3L, 6L, 43L, 45L, 2L, 5L, 51L, 11L, 1L,
50L, 4L, 14L, 49L, 15L, 10L, 13L), c(30L, 29L, 41L, 40L,
31L, 32L, 8L, 7L, 53L, 52L, 19L, 20L, 42L, 54L, 28L, 23L,
22L, 21L, 48L, 46L, 24L, 9L, 33L, 26L, 47L, 39L, 38L, 37L,
25L, 27L, 3L, 6L, 2L, 5L, 44L, 43L, 45L, 11L, 51L, 1L, 4L,
14L, 15L, 50L, 49L, 10L, 13L, 12L), c(30L, 29L, 40L, 41L,
31L, 32L, 8L, 7L, 53L, 52L, 19L, 20L, 42L, 54L, 23L, 28L,
22L, 24L, 21L, 48L, 46L, 9L, 33L, 26L, 47L, 39L, 38L, 37L,
25L, 27L, 3L, 6L, 2L, 5L, 44L, 11L, 43L, 1L, 45L, 51L, 4L,
14L, 15L, 10L, 50L, 13L, 49L, 12L, 18L), c(30L, 29L, 40L,
41L, 31L, 32L, 8L, 7L, 53L, 54L, 19L, 20L, 52L, 42L, 23L,
22L, 28L, 24L, 21L, 48L, 9L, 46L, 33L, 26L, 47L, 39L, 38L,
37L, 25L, 3L, 6L, 2L, 5L, 27L, 11L, 1L, 44L, 4L, 14L, 43L,
45L, 15L, 51L, 10L, 13L, 50L, 49L, 12L, 18L, 16L), c(30L,
29L, 40L, 41L, 31L, 32L, 8L, 7L, 54L, 53L, 19L, 20L, 23L,
52L, 22L, 42L, 24L, 28L, 9L, 21L, 48L, 46L, 33L, 26L, 47L,
39L, 38L, 37L, 25L, 3L, 6L, 2L, 5L, 11L, 27L, 1L, 4L, 14L,
15L, 44L, 10L, 43L, 13L, 45L, 51L, 12L, 50L, 49L, 18L, 16L,
17L), c(30L, 29L, 23L, 22L, 31L, 32L, 8L, 7L, 54L, 53L, 19L,
20L, 40L, 41L, 52L, 24L, 42L, 9L, 28L, 21L, 48L, 46L, 33L,
26L, 47L, 39L, 38L, 37L, 3L, 6L, 2L, 5L, 25L, 11L, 1L, 4L,
14L, 27L, 15L, 10L, 13L, 44L, 43L, 12L, 45L, 51L, 18L, 50L,
49L, 16L, 17L, 35L), c(30L, 29L, 23L, 22L, 31L, 32L, 8L,
7L, 54L, 53L, 19L, 20L, 40L, 24L, 41L, 52L, 9L, 42L, 28L,
21L, 48L, 46L, 33L, 26L, 47L, 39L, 38L, 3L, 6L, 37L, 2L,
5L, 11L, 1L, 25L, 4L, 14L, 15L, 10L, 13L, 27L, 12L, 44L,
43L, 45L, 51L, 18L, 50L, 49L, 16L, 17L, 35L, 34L), c(30L,
29L, 23L, 22L, 31L, 32L, 7L, 8L, 54L, 53L, 19L, 20L, 24L,
40L, 9L, 41L, 52L, 42L, 28L, 21L, 48L, 46L, 33L, 26L, 47L,
3L, 6L, 39L, 2L, 5L, 38L, 37L, 11L, 1L, 4L, 14L, 15L, 25L,
10L, 13L, 12L, 27L, 44L, 18L, 43L, 45L, 51L, 50L, 49L, 16L,
17L, 35L, 34L, 36L)), Sigma = 8.0762564632370211, `Standardized residuals` = structure(c(0,
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32, 8, 7, 52, 53, 19, 20, 40, 28, 21, 30, 29, 42, 41, 31, 32,
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40, 28, 54, 21, 48, 46, 23, 22, 33, 30, 29, 42, 41, 31, 32, 8,
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21, 30, 48, 19, 46, 40, 33, 54, 7, 23, 47, 22, 39, 24, 38, 37,
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44, 43, 48, 46, 42, 41, 31, 32, 26, 8, 52, 53, 21, 20, 28, 29,
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52, 53, 21, 20, 33, 28, 29, 47, 30, 19, 39, 38, 40, 37, 54, 8,
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31, 32, 26, 25, 52, 53, 21, 20, 33, 28, 47, 29, 39, 30, 19, 38,
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31, 32, 26, 8, 52, 53, 20, 21, 48, 46, 30, 19, 40, 33, 54, 47,
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1, data = Machines.O, random = ~1 | Worker, formula = score ~
1 | Worker, response.column = 4, initial.sample = 100, robs = 2)))
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MOf <-
list(`Number of rows included in Step 1` = 12, Subgroups = structure(c(1L,
2L, 3L, 4L, 5L, 6L, 4L, 2L, 5L, 3L, 6L, 1L), .Dim = c(6L, 2L), .Dimnames = list(
NULL, c("GroupNo", "groups.df1"))), `Rows by subgroup` = list(
structure(list(Observation = c(10L, 11L, 12L, 28L, 29L, 30L,
46L, 47L, 48L), Worker = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = "4", class = c("ordered", "factor"
)), Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.100015418261215,
52.300012698995246, 50.300016992158092, 63.199992088678037,
62.80001194095987, 62.200014699437098, 64.099989662253492,
66.199988194793406, 64.000003858730594)), row.names = c("10",
"11", "12", "28", "29", "30", "46", "47", "48"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(4L, 5L, 6L, 22L, 23L, 24L, 40L, 41L,
42L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "2", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.800004190474247,
52.800017306728911, 53.100008321597805, 59.700004029165804,
59.999977345031716, 59.000014059214266, 61.499984036554615,
61.700016288997055, 62.300005712008371)), row.names = c("4",
"5", "6", "22", "23", "24", "40", "41", "42"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(13L, 14L, 15L, 31L, 32L, 33L, 49L, 50L,
51L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "5", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(50.899992783998627,
51.79999844057339, 51.399996533640731, 64.799982341634859,
64.999998350602681, 65.399983036289882, 72.100010851567291,
72.000013954776875, 71.099997050762198)), row.names = c("13",
"14", "15", "31", "32", "33", "49", "50", "51"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(7L, 8L, 9L, 25L, 26L, 27L, 43L, 44L,
45L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "3", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(60.000008840809357,
60.199994043978684, 58.400008955249142, 68.59999645732411,
65.799986207004295, 69.700003515660342, 70.8000223691228,
70.599992584344704, 71.000022149245822)), row.names = c("7",
"8", "9", "25", "26", "27", "43", "44", "45"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(16L, 17L, 18L, 34L, 35L, 36L, 52L, 53L,
54L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "6", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(46.399983462321494,
44.800011309888738, 49.199993543570386, 43.700020166121483,
44.199977256271644, 43.000015614249733, 61.999986912968772,
61.399995070498328, 60.499990762286593)), row.names = c("16",
"17", "18", "34", "35", "36", "52", "53", "54"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame")), structure(list(
Observation = c(1L, 2L, 3L, 19L, 20L, 21L, 37L, 38L,
39L), Worker = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "1", class = c("ordered", "factor")),
Machine = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L), .Label = c("A", "B", "C"), class = "factor"), score = c(51.9999847465496,
52.800018242965983, 53.100021313807311, 62.100010389795997,
62.600005516019962, 63.999988679272988, 67.499977199190411,
67.19999628062493, 66.900000067831414)), row.names = c("1",
"2", "3", "19", "20", "21", "37", "38", "39"), formula = score ~
1 | Worker, FUN = function (x)
max(x, na.rm = TRUE), order.groups = TRUE, class = c("nffGroupedData",
"nfGroupedData", "groupedData", "data.frame"))), `Rows in stage` = list(
NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL,
NULL, c(8L, 19L, 20L, 28L, 29L, 30L, 40L, 41L, 42L, 52L,
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19L, 20L, 42L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L,
53L, 19L, 20L, 40L, 28L), c(30L, 29L, 42L, 41L, 31L, 32L,
8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 21L), c(30L, 29L, 42L,
41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L, 19L, 28L, 40L, 21L,
48L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L), c(29L, 30L, 42L, 41L, 31L,
32L, 8L, 7L, 52L, 53L, 20L, 19L, 28L, 40L, 21L, 48L, 46L,
54L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 20L,
19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L), c(30L, 29L, 42L,
41L, 31L, 32L, 8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 21L,
48L, 46L, 54L, 23L, 22L), c(30L, 29L, 42L, 41L, 31L, 32L,
8L, 7L, 52L, 53L, 19L, 20L, 40L, 28L, 54L, 21L, 48L, 46L,
23L, 22L, 33L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L,
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24L), c(30L, 29L, 42L, 41L, 31L, 32L, 8L, 7L, 52L, 53L, 19L,
20L, 40L, 28L, 54L, 21L, 48L, 46L, 23L, 22L, 33L, 24L, 26L
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19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L, 24L, 26L,
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19L, 28L, 40L, 21L, 48L, 46L, 54L, 23L, 22L, 33L, 26L, 24L,
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