Вы можете сделать это, используя подход tidyverse
и пакеты purrr
и broom
.
require(tidyverse)
require(broom)
df %>%
gather(var, level, -type) %>%
nest(-var) %>%
mutate(model = purrr::map(data, function(x) {
t.test(level ~ type, alternative="two.sided", conf.level=0.99,
data = x)}),
value = purrr::map(model, tidy),
conf.low = purrr::map(value, "conf.low"),
conf.high = purrr::map(value, "conf.high"),
pvalue = purrr::map(value, "p.value")) %>%
select(-data, -model, -value)
Вывод:
var conf.low conf.high pvalue
1 level1 -3.025393 4.070641 0.6941518
2 level2 -3.597754 3.356125 0.9260015
3 level3 -3.955293 3.673493 0.9210724
Пример данных:
set.seed(123)
df <- data.frame(type = rep(c("left", "right"), 25),
level1 = rnorm(50, mean = 85, sd = 5),
level2 = rnorm(50, mean = 75, sd = 5),
level3 = rnorm(50, mean = 65, sd = 5))