Sample categorical regression with table turning

table_turning.R

library(tidyverse)
library(brms)
library(langcog)

d <- tibble(subject = c(1, 1, 1, 1, 2, 2, 2, 2,
                        3, 3, 3, 3, 4, 4, 4, 4), 
            response = c("E",NA,"A","error", 
                         "E","E","E","error",
                         "A","A","E","error",
                         "A","A","A","A"), 
            condition = c(rep("Expt", 8), rep("Cntl", 8)))

ms <- d %>%
  filter(!is.na(response)) %>%
  group_by(subject, response, condition) %>%
  count %>%
  spread(response, n, fill = 0) %>%
  gather(response, n, A, E, error) %>%
  group_by(subject, condition) %>%
  mutate(prop = n / sum(n)) %>%
  group_by(condition, response) %>%
  multi_boot_standard(col = "prop")
  
ggplot(ms, 
       aes(x = response, y = mean, fill = condition)) + 
  geom_bar(stat = "identity", position = "dodge") + 
  geom_linerange(aes(ymin = ci_lower, ymax = ci_upper), 
                 position = position_dodge(width = .9))
  
mod <- brm(data = d, 
           formula = response ~ condition + (1 | subject), 
           family = "categorical")