mutate using values in a nest for each group using map - r

Question

Consider the case below for an experiment where group is different treatments, init are the initial values for each sample, change is expected change after treatment and sd_change is standard deviation of the change.
library(tidyverse)
set.seed(001)
data1 <- tibble(group = rep(c("a", "b"), each = 4),
init = rpois(8, 10)) %>%
group_by(group, init) %>%
expand(change = seq(2, 6, 2)) %>%
mutate(sd_change = 2)
as_tibble(data1)
> data1
# A tibble: 24 x 4
# Groups: group, init [8]
group init change sd_change
<chr> <int> <dbl> <dbl>
1 a 7 2 2
2 a 7 4 2
3 a 7 6 2
4 a 8 2 2
5 a 8 4 2
6 a 8 6 2
7 a 10 2 2
8 a 10 4 2
9 a 10 6 2
10 a 11 2 2
# ... with 14 more rows
I generate final values and obtain mean and variance for each group and change as below
data2a <- data1 %>%
rowwise %>%
mutate(final = rnorm(1, change, sd_change) + init) %>%
ungroup
data2a %>%
group_by(group, change) %>%
summarise(mu_start = mean(init), mu_end = mean(final),
v_start = var(init), v_end = var(final))
# A tibble: 6 x 6
# Groups: group [2]
group change mu_start mu_end v_start v_end
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 a 2 9 10.9 3.33 13.9
2 a 4 9 14.7 3.33 4.90
3 a 6 9 15.5 3.33 10.2
4 b 2 11.5 13.2 4.33 3.69
5 b 4 11.5 14.8 4.33 17.8
6 b 6 11.5 17.7 4.33 9.77
I want to repeat the above procedure R times by generating one final random value. I can do this with a for loop but I'm learning purrr and I'm stuck when summarising. See one version below:
# function to generate final values where R = 3
f <- function(n=3, x, y, z){
out <- rnorm(n, x, y)
out <- out + z
}
data2b <- data1 %>%
mutate(final = pmap(list(z = init,
x = change,
y = sd_change),
f)) %>%
ungroup
as_tibble(data2b)
# A tibble: 24 x 5
group init change sd_change final
<chr> <int> <dbl> <dbl> <list>
1 a 7 2 2 <dbl [3]>
2 a 7 4 2 <dbl [3]>
3 a 7 6 2 <dbl [3]>
4 a 8 2 2 <dbl [3]>
5 a 8 4 2 <dbl [3]>
6 a 8 6 2 <dbl [3]>
7 a 10 2 2 <dbl [3]>
8 a 10 4 2 <dbl [3]>
9 a 10 6 2 <dbl [3]>
10 a 11 2 2 <dbl [3]>
# ... with 14 more rows
summarise to get mu_end that should be a list of length R=3 in this example. The following gives an error
data2b %>%
split(.$group, .$change) %>%
mutate(mu_end = map(final, mean),
v_end = map(final, var)
Error in UseMethod("mutate_") :
no applicable method for 'mutate_' applied to an object of class "list"
The output should be like this
# A tibble: 6 x 4
# Groups: group [2]
group change mu_end v_end
<chr> <dbl> <dbl> <dbl>
1 a 2 10.9 13.9
2 a 4 14.7 4.90
3 a 6 15.5 10.2
4 b 2 13.2 3.69
5 b 4 14.8 17.8
6 b 6 17.7 9.77
but each row of mu_end and v_end should be a list of length R
any help?

Answer 1

We can either do a group_split and then map through the list of tibbles, mutate to create the mean and var of the list column 'final' by looping with map
data2b %>%
group_split(group, change) %>%
map_df(~ .x %>%
mutate(mu_end = map_dbl(final, mean),
v_end = map_dbl(final, var)))
Or without splitting
data2b %>%
group_by(group, change) %>%
mutate(mu_end = map_dbl(final, mean), v_end = map_dbl(final, var))