I have this nested dataset
dput(head(nest2, 2))
structure(list(grp = c("Avoiding", "Savoring"), data = list(structure(list(
Gender = c("Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men"), Education = structure(c(1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L,
2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 3L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L), .Label = c("Basic",
"Medium", "Higher"), class = "factor"), Efficacy = structure(c(24,
24, 29, 28, 29, 22, 30, 26, 16, 22, 26, 30, 32, 20, 24, 31,
28, 26, 25, 35, 30, 25, 28, 33, 33, 22, 24, 33, 27, 35, 26,
22, 25, 31, 22, 26, 22, 19, 26, 29, 28, 21, 23, 28, 27, 25,
22, 25, 27, 21, 25, 26, 23, 25, 21, 27, 27, 24, 17, 28, 20,
25, 35, 26, 29, 18, 23, 24, 23, 37, 25, 26, 22, 26, 30, 26,
24, 30, 19, 23, 23, 27, 20, 27, 25, 21, 12, 32, 24, 21, 26,
26, 26, 26, 20, 10, 25, 23, 17, 20, 22, 25, 23, 21, 23, 21,
20, 27, 14, 29, 24, 25, 23, 10, 31, 38, 20, 28, 29, 26, 23,
28, 21, 22, 27, 27, 27, 27, 21, 22, 23, 27, 23, 27, 22, 25,
27, 25, 20, 25, 25, 24, 27, 25, 24), format.spss = "F16.2"),
points = c(9, 10, 12, 10, 13, 11, 10, 8, 5, 6, 7, 8, 12,
6, 9, 10, 9, 11, 9, 13, 11, 10, 10, 14, 13, 9, 8, 11, 7,
13, 6, 8, 10, 10, 9, 11, 8, 5, 8, 12, 9, 9, 11, 9, 10, 10,
8, 9, 9, 10, 8, 9, 8, 9, 10, 9, 14, 8, 5, 11, 5, 7, 14, 8,
11, 8, 9, 9, 8, 15, 9, 6, 8, 10, 9, 9, 10, 12, 8, 8, 8, 13,
8, 11, 9, 9, 5, 13, 8, 7, 10, 10, 12, 10, 5, 3, 9, 9, 5,
6, 7, 8, 7, 6, 8, 6, 7, 16, 7, 10, 7, 7, 5, 4, 11, 16, 6,
9, 10, 10, 5, 9, 9, 7, 9, 12, 11, 10, 8, 10, 10, 9, 10, 10,
7, 7, 10, 8, 5, 8, 8, 9, 9, 6, 8)), row.names = c(NA, -145L
), class = c("tbl_df", "tbl", "data.frame")), structure(list(
Gender = c("Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Women", "Women", "Women", "Women",
"Women", "Women", "Women", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men"), Education = structure(c(1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L,
2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 3L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L), .Label = c("Basic",
"Medium", "Higher"), class = "factor"), Efficacy = structure(c(24,
24, 29, 28, 29, 22, 30, 26, 16, 22, 26, 30, 32, 20, 24, 31,
28, 26, 25, 35, 30, 25, 28, 33, 33, 22, 24, 33, 27, 35, 26,
22, 25, 31, 22, 26, 22, 19, 26, 29, 28, 21, 23, 28, 27, 25,
22, 25, 27, 21, 25, 26, 23, 25, 21, 27, 27, 24, 17, 28, 20,
25, 35, 26, 29, 18, 23, 24, 23, 37, 25, 26, 22, 26, 30, 26,
24, 30, 19, 23, 23, 27, 20, 27, 25, 21, 12, 32, 24, 21, 26,
26, 26, 26, 20, 10, 25, 23, 17, 20, 22, 25, 23, 21, 23, 21,
20, 27, 14, 29, 24, 25, 23, 10, 31, 38, 20, 28, 29, 26, 23,
28, 21, 22, 27, 27, 27, 27, 21, 22, 23, 27, 23, 27, 22, 25,
27, 25, 20, 25, 25, 24, 27, 25, 24), format.spss = "F16.2"),
points = c(20, 22, 25, 21, 22, 11, 21, 19, 15, 18, 23, 24,
19, 20, 20, 22, 19, 24, 22, 22, 24, 19, 19, 25, 25, 22, 19,
16, 24, 24, 22, 17, 19, 23, 21, 19, 21, 23, 23, 24, 24, 16,
21, 21, 17, 19, 17, 22, 20, 15, 16, 21, 17, 18, 19, 21, 17,
18, 23, 21, 13, 17, 24, 14, 19, 21, 21, 19, 20, 24, 21, 20,
20, 20, 18, 22, 17, 16, 21, 18, 16, 18, 21, 16, 19, 19, 10,
23, 19, 16, 18, 14, 12, 18, 17, 7, 24, 15, 21, 16, 11, 17,
21, 17, 15, 21, 12, 14, 12, 14, 16, 16, 19, 19, 18, 19, 18,
14, 20, 15, 20, 19, 16, 18, 14, 18, 16, 20, 18, 16, 17, 14,
12, 14, 14, 19, 12, 18, 13, 18, 18, 13, 23, 18, 19)), row.names = c(NA,
-145L), class = c("tbl_df", "tbl", "data.frame")))), row.names = c(NA,
-2L), class = c("tbl_df", "tbl", "data.frame"))
I have performed the t_test with the following code:
library(rstatix)
nest2 %>%
dplyr::mutate(hyp = c(rep('greater',2), 'less', 'greater'),
test = purrr::map(data, ~t_test(points ~ Gender, data = ., ref.group = 'Women', detailed = TRUE)),
sd = map(data, ~.x %>% group_by(Gender) %>% summarise(sd = sd(.data$points))))%>%
unnest(test, sd) %>%
pivot_wider(names_from = "Gender",
values_from = 'sd') %>% rename(sd1 = Men, sd2 = Women)
The output is the following
A tibble: 4 x 20
grp data hyp estim~1 estim~2 estim~3 .y. group1 group2 n1 n2 stati~4 p df conf.~5 conf.~6 method alter~7 sd1 sd2
<chr> <list> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl>
1 Avoid~ <tibble> grea~ 0.310 9.05 8.74 poin~ Women Men 107 38 0.658 5.13e-1 59.8 -0.632 1.25 T-test two.si~ 2.55 2.31
2 Savor~ <tibble> grea~ 2.64 19.2 16.6 poin~ Women Men 107 38 4.75 8.16e-6 84.9 1.53 3.74 T-test two.si~ 2.70 3.54
3 Coping <tibble> less -1.45 9.42 10.9 poin~ Women Men 107 38 -2.95 4.43e-3 66.0 -2.43 -0.467 T-test two.si~ 2.59 2.63
4 Obtai~ <tibble> grea~ 0.0305 15.9 15.9 poin~ Women Men 107 38 0.0498 9.6 e-1 61.7 -1.19 1.25 T-test two.si~ 3.29 3.10
But the alternative I would like to set are in the order (there's the alternative argument in t_test function for this that I do not know how to set)
greater
greater
less
greater
Can anyone give me a small clue? I was thinking to run twice a nested map() but I do not know how, if I am correct.
Thanks
To fix the error in your basic code you want to use an anonymous function:
library(dplyr)
library(purr)
nest2 %>%
mutate(test = map(.x = data, .f = \(.x) t_test(.x, points ~ Gender)))
To set the reference group, just add that to the function call:
nest2 %>%
mutate(test = map(.x = data, .f = \(.x) t_test(.x, points ~ Gender, ref.group = "Women")))
If you also want to vary the alternative for the tests you could add another column to your data frame and use map2. I only see two rows of data (not 4), but it would look something like this:
nest2 %>%
mutate(alternative = c("greater", "less"),
test = map2(data, alternative, \(.x, .y) {
t_test(.x, points ~ Gender, ref.group = "Women", alternative = .y)
}))