Loading libraries
library(readxl)
library(tidyverse)
library(naniar)
library(lubridate)
library(ggalluvial)
library(papaja)
library(RVAideMemoire)
library(rcompanion)
library(officer)
library(rvg)
library(kableExtra)
'%!in%' <- Negate('%in%')
coded <-
raw %>%
replace_with_na(replace = list("N")) %>%
select(ID, age, gender, order, PENS, A_B, A_D, A_E, A_G, B_B, B_D, B_E, B_G) %>%
#coding cincorrect unit counting for the "How many kinds?" trials in task A
mutate(A_B_cc = if_else(A_B %!in% c("3", "4", "5") | is.na(A_B), 1, 0),
A_D_cc = if_else(A_D %!in% c("3", "4", "5") | is.na(A_D), 1, 0),
A_E_cc = if_else(A_E == 0, 1, 0),
A_G_cc = if_else(A_G %!in% c("3", "4", "5") | is.na(A_G), 1, 0)) %>%
#coding incorrect unit counting for the "How many colors?" trials in task B
mutate(B_B_cc = if_else(B_B %!in% c("4", "5", "6") | is.na(B_B), 1, 0),
B_D_cc = if_else(B_D %!in% c("4", "5", "6") | is.na(B_D), 1, 0),
B_E_cc = if_else(B_E == 0, 1, 0),
B_G_cc = if_else(B_G %!in% c("4", "5", "6") | is.na(B_G), 1, 0)) %>%
#assign a unique group id for each child, depending on their response pattern in task A and B
mutate(B_group = group_indices(., B_B_cc, B_D_cc, B_E_cc, B_G_cc)) %>%
mutate(A_group = group_indices(., A_B_cc, A_D_cc, A_E_cc, A_G_cc))
knitr::kable(coded) %>%
kable_styling() %>%
scroll_box(width = "1000px", height = "500px")
ID | age | gender | order | PENS | A_B | A_D | A_E | A_G | B_B | B_D | B_E | B_G | A_B_cc | A_D_cc | A_E_cc | A_G_cc | B_B_cc | B_D_cc | B_E_cc | B_G_cc | B_group | A_group |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 5.668493 | female | A | 22 | 8 | 8 | 1 | 8 | 8 | 8 | 1 | 8 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
2 | 4.731507 | female | B | 8 | 4 | 3 | 1 | 4 | 5 | 3 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 1 |
4 | 5.400000 | female | B | 22 | 9 | 5 | 1 | 9 | 9 | 9 | 1 | 9 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 6 |
2814 | 6.200000 | male | A | 22 | 4 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6252 | 5.260000 | male | A | 21 | 4 | 4 | 1 | 4 | 6 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
3116 | 5.460000 | male | B | 24 | 4 | 4 | 1 | 4 | 4 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6023 | 4.310000 | female | B | 19 | 9 | 9 | 0 | 9 | 9 | 9 | 1 | 5 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 4 | 10 |
6066 | 4.190000 | female | B | 11 | 9 | 9 | 1 | 8 | 9 | 7 | 0 | 9 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 8 |
6420 | 4.100000 | female | A | 11 | 4 | 9 | 1 | 8 | 9 | 7 | 1 | 9 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 3 |
6049 | 4.410000 | male | B | 8 | 11 | N | 1 | 7 | 10 | 6 | 1 | 6 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 3 | 8 |
6134 | 5.630000 | male | A | 22 | 4 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6065 | 5.570000 | male | B | 19 | 5 | 4 | 1 | 5 | 4 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6147 | 4.640000 | female | A | 18 | 10 | N | 0 | 9 | 10 | 5 | 1 | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 3 | 10 |
6150 | 4.270000 | male | B | 10 | 9 | 9 | 1 | 8 | 8 | 9 | 1 | 9 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
6148 | 4.240000 | male | A | 7 | 9 | 7 | 1 | 4 | 9 | 5 | 1 | 5 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 7 |
6100 | 4.100000 | male | A | 6 | 8 | 8 | 0 | 9 | 9 | 8 | 0 | 9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | 10 |
3238 | 5.610000 | female | B | 23 | 5 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
3350 | 6.250000 | male | B | 21 | N | 9 | 1 | 9 | 10 | 9 | 1 | 9 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
6238 | 4.610000 | male | A | 9 | 5 | 8 | 0 | 9 | 15 | 10 | 1 | 10 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 5 | 4 |
6414 | 4.500000 | male | B | 23 | 4 | 4 | 1 | 4 | 9 | N | 1 | 9 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 5 | 1 |
6075 | 4.290000 | female | A | 18 | 4 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6076 | 5.260000 | female | B | 24 | 9 | 9 | 1 | 9 | 5 | 5 | 1 | 5 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 8 |
6059 | 4.060000 | female | A | 13 | 9 | 4 | 1 | 4 | 4 | 4 | 1 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 5 |
6031 | 4.040000 | male | B | 11 | 9 | 9 | 1 | 9 | 9 | 9 | 0 | 9 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 8 |
6102 | 5.190000 | male | A | 18 | N | 9 | 1 | 9 | N | 5 | 1 | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 3 | 8 |
6112 | 4.040000 | male | A | NA | 9 | N | 0 | 4 | 10 | N | 1 | 5 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 4 | 9 |
6218 | 4.520000 | male | B | 9 | 13 | 10 | 0 | 9 | 12 | 10 | 0 | 10 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | 10 |
6136 | 5.010000 | male | B | 24 | N | N | 1 | N | N | N | 1 | N | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
6253 | 4.710000 | male | A | 23 | 4 | 4 | 1 | 4 | 15 | 8 | 1 | 6 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 | 1 |
6227 | 4.460000 | male | A | 17 | 9 | N | 0 | 10 | 9 | 9 | 0 | 9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | 10 |
6143 | 5.580000 | female | B | 22 | 4 | 4 | 1 | 4 | 7 | 6 | 1 | 5 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 1 |
6024 | 5.230000 | male | A | 9 | 9 | 9 | 1 | 9 | 9 | 5 | 1 | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 3 | 8 |
6056 | 5.510000 | male | B | 22 | 5 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6050 | 4.840000 | male | B | 20 | 5 | 9 | 1 | 4 | 9 | 11 | 0 | 5 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 6 | 2 |
3363 | 5.220000 | female | A | 24 | 9 | N | 1 | N | 5 | 9 | 1 | 5 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2 | 8 |
6174 | 4.840000 | male | B | 16 | 4 | 4 | 1 | 4 | 5 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
6002 | 4.500000 | male | A | 7 | 4 | N | 1 | 9 | 10 | 9 | 1 | 5 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 4 | 3 |
6142 | 5.200000 | female | B | 22 | 8 | 8 | 0 | 8 | 8 | 8 | 1 | 8 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 5 | 10 |
3373 | 5.200000 | male | A | 24 | N | N | 1 | N | 6 | N | 1 | 5 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2 | 8 |
6145 | 5.930000 | male | A | 22 | 6 | 9 | 1 | 9 | 9 | 9 | 1 | 5 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 4 | 8 |
3306 | 5.700000 | female | B | 21 | 5 | 5 | 1 | 5 | 6 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
3196 | 5.420000 | female | A | 21 | 4 | 4 | 1 | 4 | 8 | 7 | 1 | 9 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 5 | 1 |
6078 | 5.190000 | female | B | 22 | 4 | 4 | 1 | 4 | 7 | 5 | 1 | 5 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 1 |
3122 | 5.280000 | female | B | 22 | 9 | 9 | 1 | 9 | 9 | 9 | 1 | 9 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
6073 | 4.010000 | female | A | 8 | 7 | 8 | 1 | N | 9 | 10 | 1 | N | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 5 | 8 |
5 | 3.265753 | male | A | 16 | 9 | 4 | 1 | 4 | 9 | 5 | 1 | 5 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 5 |
#dataframe for visualization
grouped <-
coded %>%
select(ID, A_B_cc:A_group, PENS, age) %>%
gather(trial, incorrect_unit_count, 2:9) %>%
separate(trial, into = c("task", "trial"), extra = "merge", sep = "_") %>%
arrange(ID)
knitr::kable(grouped) %>%
kable_styling() %>%
scroll_box(width = "1000px", height = "500px")
ID | B_group | A_group | PENS | age | task | trial | incorrect_unit_count |
---|---|---|---|---|---|---|---|
1 | 5 | 8 | 22 | 5.668493 | A | B_cc | 1 |
1 | 5 | 8 | 22 | 5.668493 | A | D_cc | 1 |
1 | 5 | 8 | 22 | 5.668493 | A | E_cc | 0 |
1 | 5 | 8 | 22 | 5.668493 | A | G_cc | 1 |
1 | 5 | 8 | 22 | 5.668493 | B | B_cc | 1 |
1 | 5 | 8 | 22 | 5.668493 | B | D_cc | 1 |
1 | 5 | 8 | 22 | 5.668493 | B | E_cc | 0 |
1 | 5 | 8 | 22 | 5.668493 | B | G_cc | 1 |
2 | 2 | 1 | 8 | 4.731507 | A | B_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | A | D_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | A | E_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | A | G_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | B | B_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | B | D_cc | 1 |
2 | 2 | 1 | 8 | 4.731507 | B | E_cc | 0 |
2 | 2 | 1 | 8 | 4.731507 | B | G_cc | 0 |
4 | 5 | 6 | 22 | 5.400000 | A | B_cc | 1 |
4 | 5 | 6 | 22 | 5.400000 | A | D_cc | 0 |
4 | 5 | 6 | 22 | 5.400000 | A | E_cc | 0 |
4 | 5 | 6 | 22 | 5.400000 | A | G_cc | 1 |
4 | 5 | 6 | 22 | 5.400000 | B | B_cc | 1 |
4 | 5 | 6 | 22 | 5.400000 | B | D_cc | 1 |
4 | 5 | 6 | 22 | 5.400000 | B | E_cc | 0 |
4 | 5 | 6 | 22 | 5.400000 | B | G_cc | 1 |
5 | 3 | 5 | 16 | 3.265753 | A | B_cc | 1 |
5 | 3 | 5 | 16 | 3.265753 | A | D_cc | 0 |
5 | 3 | 5 | 16 | 3.265753 | A | E_cc | 0 |
5 | 3 | 5 | 16 | 3.265753 | A | G_cc | 0 |
5 | 3 | 5 | 16 | 3.265753 | B | B_cc | 1 |
5 | 3 | 5 | 16 | 3.265753 | B | D_cc | 0 |
5 | 3 | 5 | 16 | 3.265753 | B | E_cc | 0 |
5 | 3 | 5 | 16 | 3.265753 | B | G_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | A | B_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | A | D_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | A | E_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | A | G_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | B | B_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | B | D_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | B | E_cc | 0 |
2814 | 1 | 1 | 22 | 6.200000 | B | G_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | A | B_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | A | D_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | A | E_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | A | G_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | B | B_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | B | D_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | B | E_cc | 0 |
3116 | 1 | 1 | 24 | 5.460000 | B | G_cc | 0 |
3122 | 5 | 8 | 22 | 5.280000 | A | B_cc | 1 |
3122 | 5 | 8 | 22 | 5.280000 | A | D_cc | 1 |
3122 | 5 | 8 | 22 | 5.280000 | A | E_cc | 0 |
3122 | 5 | 8 | 22 | 5.280000 | A | G_cc | 1 |
3122 | 5 | 8 | 22 | 5.280000 | B | B_cc | 1 |
3122 | 5 | 8 | 22 | 5.280000 | B | D_cc | 1 |
3122 | 5 | 8 | 22 | 5.280000 | B | E_cc | 0 |
3122 | 5 | 8 | 22 | 5.280000 | B | G_cc | 1 |
3196 | 5 | 1 | 21 | 5.420000 | A | B_cc | 0 |
3196 | 5 | 1 | 21 | 5.420000 | A | D_cc | 0 |
3196 | 5 | 1 | 21 | 5.420000 | A | E_cc | 0 |
3196 | 5 | 1 | 21 | 5.420000 | A | G_cc | 0 |
3196 | 5 | 1 | 21 | 5.420000 | B | B_cc | 1 |
3196 | 5 | 1 | 21 | 5.420000 | B | D_cc | 1 |
3196 | 5 | 1 | 21 | 5.420000 | B | E_cc | 0 |
3196 | 5 | 1 | 21 | 5.420000 | B | G_cc | 1 |
3238 | 1 | 1 | 23 | 5.610000 | A | B_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | A | D_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | A | E_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | A | G_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | B | B_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | B | D_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | B | E_cc | 0 |
3238 | 1 | 1 | 23 | 5.610000 | B | G_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | A | B_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | A | D_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | A | E_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | A | G_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | B | B_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | B | D_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | B | E_cc | 0 |
3306 | 1 | 1 | 21 | 5.700000 | B | G_cc | 0 |
3350 | 5 | 8 | 21 | 6.250000 | A | B_cc | 1 |
3350 | 5 | 8 | 21 | 6.250000 | A | D_cc | 1 |
3350 | 5 | 8 | 21 | 6.250000 | A | E_cc | 0 |
3350 | 5 | 8 | 21 | 6.250000 | A | G_cc | 1 |
3350 | 5 | 8 | 21 | 6.250000 | B | B_cc | 1 |
3350 | 5 | 8 | 21 | 6.250000 | B | D_cc | 1 |
3350 | 5 | 8 | 21 | 6.250000 | B | E_cc | 0 |
3350 | 5 | 8 | 21 | 6.250000 | B | G_cc | 1 |
3363 | 2 | 8 | 24 | 5.220000 | A | B_cc | 1 |
3363 | 2 | 8 | 24 | 5.220000 | A | D_cc | 1 |
3363 | 2 | 8 | 24 | 5.220000 | A | E_cc | 0 |
3363 | 2 | 8 | 24 | 5.220000 | A | G_cc | 1 |
3363 | 2 | 8 | 24 | 5.220000 | B | B_cc | 0 |
3363 | 2 | 8 | 24 | 5.220000 | B | D_cc | 1 |
3363 | 2 | 8 | 24 | 5.220000 | B | E_cc | 0 |
3363 | 2 | 8 | 24 | 5.220000 | B | G_cc | 0 |
3373 | 2 | 8 | 24 | 5.200000 | A | B_cc | 1 |
3373 | 2 | 8 | 24 | 5.200000 | A | D_cc | 1 |
3373 | 2 | 8 | 24 | 5.200000 | A | E_cc | 0 |
3373 | 2 | 8 | 24 | 5.200000 | A | G_cc | 1 |
3373 | 2 | 8 | 24 | 5.200000 | B | B_cc | 0 |
3373 | 2 | 8 | 24 | 5.200000 | B | D_cc | 1 |
3373 | 2 | 8 | 24 | 5.200000 | B | E_cc | 0 |
3373 | 2 | 8 | 24 | 5.200000 | B | G_cc | 0 |
6002 | 4 | 3 | 7 | 4.500000 | A | B_cc | 0 |
6002 | 4 | 3 | 7 | 4.500000 | A | D_cc | 1 |
6002 | 4 | 3 | 7 | 4.500000 | A | E_cc | 0 |
6002 | 4 | 3 | 7 | 4.500000 | A | G_cc | 1 |
6002 | 4 | 3 | 7 | 4.500000 | B | B_cc | 1 |
6002 | 4 | 3 | 7 | 4.500000 | B | D_cc | 1 |
6002 | 4 | 3 | 7 | 4.500000 | B | E_cc | 0 |
6002 | 4 | 3 | 7 | 4.500000 | B | G_cc | 0 |
6023 | 4 | 10 | 19 | 4.310000 | A | B_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | A | D_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | A | E_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | A | G_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | B | B_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | B | D_cc | 1 |
6023 | 4 | 10 | 19 | 4.310000 | B | E_cc | 0 |
6023 | 4 | 10 | 19 | 4.310000 | B | G_cc | 0 |
6024 | 3 | 8 | 9 | 5.230000 | A | B_cc | 1 |
6024 | 3 | 8 | 9 | 5.230000 | A | D_cc | 1 |
6024 | 3 | 8 | 9 | 5.230000 | A | E_cc | 0 |
6024 | 3 | 8 | 9 | 5.230000 | A | G_cc | 1 |
6024 | 3 | 8 | 9 | 5.230000 | B | B_cc | 1 |
6024 | 3 | 8 | 9 | 5.230000 | B | D_cc | 0 |
6024 | 3 | 8 | 9 | 5.230000 | B | E_cc | 0 |
6024 | 3 | 8 | 9 | 5.230000 | B | G_cc | 0 |
6031 | 7 | 8 | 11 | 4.040000 | A | B_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | A | D_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | A | E_cc | 0 |
6031 | 7 | 8 | 11 | 4.040000 | A | G_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | B | B_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | B | D_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | B | E_cc | 1 |
6031 | 7 | 8 | 11 | 4.040000 | B | G_cc | 1 |
6049 | 3 | 8 | 8 | 4.410000 | A | B_cc | 1 |
6049 | 3 | 8 | 8 | 4.410000 | A | D_cc | 1 |
6049 | 3 | 8 | 8 | 4.410000 | A | E_cc | 0 |
6049 | 3 | 8 | 8 | 4.410000 | A | G_cc | 1 |
6049 | 3 | 8 | 8 | 4.410000 | B | B_cc | 1 |
6049 | 3 | 8 | 8 | 4.410000 | B | D_cc | 0 |
6049 | 3 | 8 | 8 | 4.410000 | B | E_cc | 0 |
6049 | 3 | 8 | 8 | 4.410000 | B | G_cc | 0 |
6050 | 6 | 2 | 20 | 4.840000 | A | B_cc | 0 |
6050 | 6 | 2 | 20 | 4.840000 | A | D_cc | 1 |
6050 | 6 | 2 | 20 | 4.840000 | A | E_cc | 0 |
6050 | 6 | 2 | 20 | 4.840000 | A | G_cc | 0 |
6050 | 6 | 2 | 20 | 4.840000 | B | B_cc | 1 |
6050 | 6 | 2 | 20 | 4.840000 | B | D_cc | 1 |
6050 | 6 | 2 | 20 | 4.840000 | B | E_cc | 1 |
6050 | 6 | 2 | 20 | 4.840000 | B | G_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | A | B_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | A | D_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | A | E_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | A | G_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | B | B_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | B | D_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | B | E_cc | 0 |
6056 | 1 | 1 | 22 | 5.510000 | B | G_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | A | B_cc | 1 |
6059 | 1 | 5 | 13 | 4.060000 | A | D_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | A | E_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | A | G_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | B | B_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | B | D_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | B | E_cc | 0 |
6059 | 1 | 5 | 13 | 4.060000 | B | G_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | A | B_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | A | D_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | A | E_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | A | G_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | B | B_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | B | D_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | B | E_cc | 0 |
6065 | 1 | 1 | 19 | 5.570000 | B | G_cc | 0 |
6066 | 7 | 8 | 11 | 4.190000 | A | B_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | A | D_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | A | E_cc | 0 |
6066 | 7 | 8 | 11 | 4.190000 | A | G_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | B | B_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | B | D_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | B | E_cc | 1 |
6066 | 7 | 8 | 11 | 4.190000 | B | G_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | A | B_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | A | D_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | A | E_cc | 0 |
6073 | 5 | 8 | 8 | 4.010000 | A | G_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | B | B_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | B | D_cc | 1 |
6073 | 5 | 8 | 8 | 4.010000 | B | E_cc | 0 |
6073 | 5 | 8 | 8 | 4.010000 | B | G_cc | 1 |
6075 | 1 | 1 | 18 | 4.290000 | A | B_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | A | D_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | A | E_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | A | G_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | B | B_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | B | D_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | B | E_cc | 0 |
6075 | 1 | 1 | 18 | 4.290000 | B | G_cc | 0 |
6076 | 1 | 8 | 24 | 5.260000 | A | B_cc | 1 |
6076 | 1 | 8 | 24 | 5.260000 | A | D_cc | 1 |
6076 | 1 | 8 | 24 | 5.260000 | A | E_cc | 0 |
6076 | 1 | 8 | 24 | 5.260000 | A | G_cc | 1 |
6076 | 1 | 8 | 24 | 5.260000 | B | B_cc | 0 |
6076 | 1 | 8 | 24 | 5.260000 | B | D_cc | 0 |
6076 | 1 | 8 | 24 | 5.260000 | B | E_cc | 0 |
6076 | 1 | 8 | 24 | 5.260000 | B | G_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | A | B_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | A | D_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | A | E_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | A | G_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | B | B_cc | 1 |
6078 | 3 | 1 | 22 | 5.190000 | B | D_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | B | E_cc | 0 |
6078 | 3 | 1 | 22 | 5.190000 | B | G_cc | 0 |
6100 | 7 | 10 | 6 | 4.100000 | A | B_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | A | D_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | A | E_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | A | G_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | B | B_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | B | D_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | B | E_cc | 1 |
6100 | 7 | 10 | 6 | 4.100000 | B | G_cc | 1 |
6102 | 3 | 8 | 18 | 5.190000 | A | B_cc | 1 |
6102 | 3 | 8 | 18 | 5.190000 | A | D_cc | 1 |
6102 | 3 | 8 | 18 | 5.190000 | A | E_cc | 0 |
6102 | 3 | 8 | 18 | 5.190000 | A | G_cc | 1 |
6102 | 3 | 8 | 18 | 5.190000 | B | B_cc | 1 |
6102 | 3 | 8 | 18 | 5.190000 | B | D_cc | 0 |
6102 | 3 | 8 | 18 | 5.190000 | B | E_cc | 0 |
6102 | 3 | 8 | 18 | 5.190000 | B | G_cc | 0 |
6112 | 4 | 9 | NA | 4.040000 | A | B_cc | 1 |
6112 | 4 | 9 | NA | 4.040000 | A | D_cc | 1 |
6112 | 4 | 9 | NA | 4.040000 | A | E_cc | 1 |
6112 | 4 | 9 | NA | 4.040000 | A | G_cc | 0 |
6112 | 4 | 9 | NA | 4.040000 | B | B_cc | 1 |
6112 | 4 | 9 | NA | 4.040000 | B | D_cc | 1 |
6112 | 4 | 9 | NA | 4.040000 | B | E_cc | 0 |
6112 | 4 | 9 | NA | 4.040000 | B | G_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | A | B_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | A | D_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | A | E_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | A | G_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | B | B_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | B | D_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | B | E_cc | 0 |
6134 | 1 | 1 | 22 | 5.630000 | B | G_cc | 0 |
6136 | 5 | 8 | 24 | 5.010000 | A | B_cc | 1 |
6136 | 5 | 8 | 24 | 5.010000 | A | D_cc | 1 |
6136 | 5 | 8 | 24 | 5.010000 | A | E_cc | 0 |
6136 | 5 | 8 | 24 | 5.010000 | A | G_cc | 1 |
6136 | 5 | 8 | 24 | 5.010000 | B | B_cc | 1 |
6136 | 5 | 8 | 24 | 5.010000 | B | D_cc | 1 |
6136 | 5 | 8 | 24 | 5.010000 | B | E_cc | 0 |
6136 | 5 | 8 | 24 | 5.010000 | B | G_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | A | B_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | A | D_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | A | E_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | A | G_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | B | B_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | B | D_cc | 1 |
6142 | 5 | 10 | 22 | 5.200000 | B | E_cc | 0 |
6142 | 5 | 10 | 22 | 5.200000 | B | G_cc | 1 |
6143 | 3 | 1 | 22 | 5.580000 | A | B_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | A | D_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | A | E_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | A | G_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | B | B_cc | 1 |
6143 | 3 | 1 | 22 | 5.580000 | B | D_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | B | E_cc | 0 |
6143 | 3 | 1 | 22 | 5.580000 | B | G_cc | 0 |
6145 | 4 | 8 | 22 | 5.930000 | A | B_cc | 1 |
6145 | 4 | 8 | 22 | 5.930000 | A | D_cc | 1 |
6145 | 4 | 8 | 22 | 5.930000 | A | E_cc | 0 |
6145 | 4 | 8 | 22 | 5.930000 | A | G_cc | 1 |
6145 | 4 | 8 | 22 | 5.930000 | B | B_cc | 1 |
6145 | 4 | 8 | 22 | 5.930000 | B | D_cc | 1 |
6145 | 4 | 8 | 22 | 5.930000 | B | E_cc | 0 |
6145 | 4 | 8 | 22 | 5.930000 | B | G_cc | 0 |
6147 | 3 | 10 | 18 | 4.640000 | A | B_cc | 1 |
6147 | 3 | 10 | 18 | 4.640000 | A | D_cc | 1 |
6147 | 3 | 10 | 18 | 4.640000 | A | E_cc | 1 |
6147 | 3 | 10 | 18 | 4.640000 | A | G_cc | 1 |
6147 | 3 | 10 | 18 | 4.640000 | B | B_cc | 1 |
6147 | 3 | 10 | 18 | 4.640000 | B | D_cc | 0 |
6147 | 3 | 10 | 18 | 4.640000 | B | E_cc | 0 |
6147 | 3 | 10 | 18 | 4.640000 | B | G_cc | 0 |
6148 | 3 | 7 | 7 | 4.240000 | A | B_cc | 1 |
6148 | 3 | 7 | 7 | 4.240000 | A | D_cc | 1 |
6148 | 3 | 7 | 7 | 4.240000 | A | E_cc | 0 |
6148 | 3 | 7 | 7 | 4.240000 | A | G_cc | 0 |
6148 | 3 | 7 | 7 | 4.240000 | B | B_cc | 1 |
6148 | 3 | 7 | 7 | 4.240000 | B | D_cc | 0 |
6148 | 3 | 7 | 7 | 4.240000 | B | E_cc | 0 |
6148 | 3 | 7 | 7 | 4.240000 | B | G_cc | 0 |
6150 | 5 | 8 | 10 | 4.270000 | A | B_cc | 1 |
6150 | 5 | 8 | 10 | 4.270000 | A | D_cc | 1 |
6150 | 5 | 8 | 10 | 4.270000 | A | E_cc | 0 |
6150 | 5 | 8 | 10 | 4.270000 | A | G_cc | 1 |
6150 | 5 | 8 | 10 | 4.270000 | B | B_cc | 1 |
6150 | 5 | 8 | 10 | 4.270000 | B | D_cc | 1 |
6150 | 5 | 8 | 10 | 4.270000 | B | E_cc | 0 |
6150 | 5 | 8 | 10 | 4.270000 | B | G_cc | 1 |
6174 | 1 | 1 | 16 | 4.840000 | A | B_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | A | D_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | A | E_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | A | G_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | B | B_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | B | D_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | B | E_cc | 0 |
6174 | 1 | 1 | 16 | 4.840000 | B | G_cc | 0 |
6218 | 7 | 10 | 9 | 4.520000 | A | B_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | A | D_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | A | E_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | A | G_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | B | B_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | B | D_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | B | E_cc | 1 |
6218 | 7 | 10 | 9 | 4.520000 | B | G_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | A | B_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | A | D_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | A | E_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | A | G_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | B | B_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | B | D_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | B | E_cc | 1 |
6227 | 7 | 10 | 17 | 4.460000 | B | G_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | A | B_cc | 0 |
6238 | 5 | 4 | 9 | 4.610000 | A | D_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | A | E_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | A | G_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | B | B_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | B | D_cc | 1 |
6238 | 5 | 4 | 9 | 4.610000 | B | E_cc | 0 |
6238 | 5 | 4 | 9 | 4.610000 | B | G_cc | 1 |
6252 | 1 | 1 | 21 | 5.260000 | A | B_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | A | D_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | A | E_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | A | G_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | B | B_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | B | D_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | B | E_cc | 0 |
6252 | 1 | 1 | 21 | 5.260000 | B | G_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | A | B_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | A | D_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | A | E_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | A | G_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | B | B_cc | 1 |
6253 | 4 | 1 | 23 | 4.710000 | B | D_cc | 1 |
6253 | 4 | 1 | 23 | 4.710000 | B | E_cc | 0 |
6253 | 4 | 1 | 23 | 4.710000 | B | G_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | A | B_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | A | D_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | A | E_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | A | G_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | B | B_cc | 1 |
6414 | 5 | 1 | 23 | 4.500000 | B | D_cc | 1 |
6414 | 5 | 1 | 23 | 4.500000 | B | E_cc | 0 |
6414 | 5 | 1 | 23 | 4.500000 | B | G_cc | 1 |
6420 | 5 | 3 | 11 | 4.100000 | A | B_cc | 0 |
6420 | 5 | 3 | 11 | 4.100000 | A | D_cc | 1 |
6420 | 5 | 3 | 11 | 4.100000 | A | E_cc | 0 |
6420 | 5 | 3 | 11 | 4.100000 | A | G_cc | 1 |
6420 | 5 | 3 | 11 | 4.100000 | B | B_cc | 1 |
6420 | 5 | 3 | 11 | 4.100000 | B | D_cc | 1 |
6420 | 5 | 3 | 11 | 4.100000 | B | E_cc | 0 |
6420 | 5 | 3 | 11 | 4.100000 | B | G_cc | 1 |
#for task A "How many kinds?"
flow_A <-
grouped %>%
filter(task == "A") %>%
mutate(incorrect_unit_count = as.factor(incorrect_unit_count),
A_group = as.factor(A_group)) %>%
ggplot(aes(x = trial, stratum = incorrect_unit_count, alluvium = ID,
fill = A_group, label = incorrect_unit_count)) +
scale_fill_brewer(type = "qual", palette = "Set3") +
geom_flow(stat = "alluvium", lode.guidance = "rightleft",
color = "darkgray") +
geom_stratum() +
theme_apa()
flow_A
#print alluvial plot for task "How many kinds?"
#four bars represent binary responses to count_array, count_sorted, give_blocks and _count_withblocks
#children with the same color responded in the same way
#for task B "How many colors?"
flow_B <-
grouped %>%
filter(task == "B") %>%
mutate(incorrect_unit_count = as.factor(incorrect_unit_count),
B_group = as.factor(B_group)) %>%
ggplot(aes(x = trial, stratum = incorrect_unit_count, alluvium = ID,
fill = B_group, label = incorrect_unit_count)) +
scale_fill_brewer(type = "qual", palette = "Set3") +
geom_flow(stat = "alluvium", lode.guidance = "rightleft",
color = "darkgray") +
geom_stratum() +
theme_apa()
flow_B
#print alluvial plot for task "How many colors?"
#four bars represent binary responses to count_array, count_sorted, give_blocks and _count_withblocks
#children with the same color responded in the same way
Overlap between group membership in task a and task b:
A1 “always correct” (n=16) -> B1 “always correct” (n=12) = overlap n=10 A8 “only blocks” (n=15) -> B5 “only blocks” (n=12) = overlap n=6 A10 “always wrong” (n=6) -> B7 “always wrong” (n=5) = overlap n=3 A5 “only wrong in randon” (n=2) -> B3 “only wrong in random” (n=8) = overlap n=1
in total 20/46 children (43%) of children demonstrated the exact same pattern of performance on the different tasks
#Cochran's Q test for task A "How many kinds?"
cochran_A <-
coded %>%
select(ID, 14:17) %>%
gather("trial", "incorrect_unit_count", 2:5) %>%
separate(trial, into = c("task", "trial"), extra = "merge", sep = "_")
print(cochran_A_results <- cochran.qtest(incorrect_unit_count ~ trial | ID,
data = cochran_A))
##
## Cochran's Q test
##
## data: incorrect_unit_count by trial, block = ID
## Q = 38.6842, df = 3, p-value = 2.025e-08
## alternative hypothesis: true difference in probabilities is not equal to 0
## sample estimates:
## proba in group <NA> <NA> <NA>
## 0.5652174 0.5869565 0.1739130 0.5434783
#Q = 38.6842, df = 3, p-value = 2.025e-08 with probabilities 57% --> 59% --> 17% --> 54%
#Cochran's Q test for task B "How many colors?"
cochran_B <-
coded %>%
select(ID, 18:21) %>%
gather("trial", "incorrect_unit_count", 2:5) %>%
separate(trial, into = c("task", "trial"), extra = "merge", sep = "_")
print(cochran_B_results <- cochran.qtest(incorrect_unit_count ~ trial | ID,
data = cochran_B))
##
## Cochran's Q test
##
## data: incorrect_unit_count by trial, block = ID
## Q = 47.2174, df = 3, p-value = 3.125e-10
## alternative hypothesis: true difference in probabilities is not equal to 0
## sample estimates:
## proba in group <NA> <NA> <NA>
## 0.6739130 0.5652174 0.1304348 0.3695652
#Q = 47.2174, df = 3, p-value = 3.125e-10 with probabilities 67% --> 57% --> 13% --> 37%
#post-hoc for task A "kinds"
pairwiseMcnemar(incorrect_unit_count ~ trial|ID, data = cochran_A, test = "exact", method = "none", digits = 3)
## $Test.method
## Test
## 1 exact
##
## $Adustment.method
## Method
## 1 none
##
## $Pairwise
## Comparison Successes Trials p.value p.adjust
## 1 B_cc - D_cc = 0 3 7 1 1.00e+00
## 2 B_cc - E_cc = 0 19 20 4.01e-05 4.01e-05
## 3 B_cc - G_cc = 0 4 7 1 1.00e+00
## 4 D_cc - E_cc = 0 19 19 3.81e-06 3.81e-06
## 5 D_cc - G_cc = 0 3 4 0.625 6.25e-01
## 6 E_cc - G_cc = 0 1 19 7.63e-05 7.63e-05
pairwiseMcnemar(incorrect_unit_count ~ trial|ID, data = cochran_B, test = "exact", method = "none", digits = 3)
## $Test.method
## Test
## 1 exact
##
## $Adustment.method
## Method
## 1 none
##
## $Pairwise
## Comparison Successes Trials p.value p.adjust
## 1 B_cc - D_cc = 0 8 11 0.227 2.27e-01
## 2 B_cc - E_cc = 0 25 25 5.96e-08 5.96e-08
## 3 B_cc - G_cc = 0 14 14 0.000122 1.22e-04
## 4 D_cc - E_cc = 0 20 20 1.91e-06 1.91e-06
## 5 D_cc - G_cc = 0 9 9 0.00391 3.91e-03
## 6 E_cc - G_cc = 0 1 13 0.00342 3.42e-03