Create 100 2x2 contingency tables with specified probabilities of each column

[shhhhh]

I would like to generate a large number of 2x2 contingency tables in r studio, using a specified probability in each column.
If i had an example where a column has title '1', then there would be a 20% chance that a person could be allocated to that row, otherwise, the second row - with a total number of 20 people.

How can i randomly generate these?

[williaml]

Can you provide a reproducible example of your dataset?

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[shhhhh]

The data needs to be randomly generated. For example, we have 20 males who are randomly allocated in either attending or not attending a sporting event (20% chance of attending) and 20 females who are either attending or not attending (20% chance of attending). How could i generate 100 contingency tables of these random occurrences?

I believe i may have to use a for loop

[nirgrahamuk]

myran <- function(num_males, prob_attend_male,
                  num_fem, prob_attend_fem) {
  mframe <- data.frame(
    M_or_F = rep("M", num_males),
    attend = sample(c(0, 1), 
    size = num_males, 
    prob = c(1 - prob_attend_male, prob_attend_male), replace = TRUE)
  )
  fframe <- data.frame(
    M_or_F = rep("F", num_fem),
    attend = sample(c(0, 1), 
    size = num_fem, 
    prob = c(1 - prob_attend_fem, prob_attend_fem), replace = TRUE)
  )

  together <- rbind(mframe, fframe)

  table(
    together$M_or_F,
    together$attend
  )
}

# once
myran(20,.2,20,.2)

# 100 times  (library(purrr))
purrr::map(1:100,~myran(20,.2,20,.2))

[Yarnabrina]

@nirgrahamuk

sample(c(0, 1), 
    size = num_males, 
    prob = c(1 - prob_attend_male, prob_attend_male), replace = TRUE)

I want to replace this part with the following:

rbinom(num_males, 1, prob_attend_male)

Does the same thing, just in a concise way.