Bayes factor for contingency table

contingency_bf.R

library(tidyverse)
library(BayesFactor)

# set seed for reproducibility
set.seed(234)

# define population-level parameters
p_text_yes <- 0.5
p_video_yes <- 0.5

# sample size
n <- 300

# simulate data using population-level parameters
data <- tibble(
  medium = rep(c("text", "video"), each = n),
  judgement = rbinom(2 * n, 
                     size = 1, 
                     prob = if_else(medium == "text", p_text_yes, p_video_yes))
) %>% 
  mutate(judgement = case_when(judgement == 1 ~ "yes", 
                               judgement == 0 ~ "no"))

# collapse into a contingency table
contingency_table <- table(data$medium, 
                           data$judgement)

# Calculate the Bayes factor for the contingency table
bf <- contingencyTableBF(contingency_table, 
                         sampleType = "indepMulti", 
                         fixedMargin = "rows")

# get bf for null vs alternative
1/bf