How to easily generate/simulate meaningful example data for modelling: e.g. telling that give me n rows of data, for 2 groups, their sex distributions and mean age should differ by X and Y units, respectively? Is there a simple way for doing it automatically? Any packages?
For example, what would be the simplest way for generating such data?
- groups: two groups: A, B
- sex: different sex distributions: A 30%, B 70%
- age: different mean ages: A 50, B 70
PS! Tidyverse solutions are especially welcome.
My best try so far is still quite a lot of code:
n=100
d = bind_rows(
#group A females
tibble(group = rep("A"),
sex = rep("Female"),
age = rnorm(n*0.4, 50, 4)),
#group B females
tibble(group = rep("B"),
sex = rep("Female"),
age = rnorm(n*0.3, 45, 4)),
#group A males
tibble(group = rep("A"),
sex = rep("Male"),
age = rnorm(n*0.20, 60, 6)),
#group B males
tibble(group = rep("B"),
sex = rep("Male"),
age = rnorm(n*0.10, 55, 4)))
d %>% group_by(group, sex) %>%
summarise(n = n(),
mean_age = mean(age))
There are lots of ways to sample from vectors and to draw from random distributions in R. For example, the data set you requested could be created like this:
And we can use the tidyverse to show it does what was expected: