Simulation of ratings

### Simulate observers
library(brms)

obs <- 16 # How many observers?
trials <- 70 # How many trials per filter

# Plausible ratings
high <- c(rep(2,8),rep(3,27),rep(4,25),rep(5,10))
med <- c(rep(1,4),rep(2,22),rep(3,32),rep(4,11),rep(5,2))
low <- c(rep(1,15),rep(2,31),rep(3,16),rep(4,4))

set.seed(42) # Set seed for reproducibility

# All observers like the non-filtered equally
filterNon <- sample(high, trials*obs, replace = T)
# Half observers dislike one filter particularly
filterBad <- sample(low, trials*(obs/2), replace = T)
# Rest of observers dislike filters equally
filterMed <- sample(med, trials*(obs*1.5), replace = T)

# Create data frame
ratings <- c(filterNon,filterBad,filterMed)
filter <- sort(rep(c("0: None","1: Bad","2: Medium"),obs*trials))
id <- factor(rep(sort(rep(1:obs,trials)),3))
results <- data.frame(ratings,filter,id)

# Create brms model
results$rating <- ordered(results$ratings)
# Rating for each filter, random effect per id
mfilter <- brm(rating ~ filter + (filter|id), data = results,
             family = cumulative(threshold = "flexible"),
             chains = 2, cores = 2, iter=3000)

# Plot each observer as understood by model
conditional_effects(mfilter)
consub <- make_conditions(results, vars = c("id"))

# Look at categorical model
conditional_effects(
  mfilter,
  "filter",
  conditions = consub,
  re_formula = NULL, categorical = F
)

# EXPERIMENT 2
set.seed(101) # Set seed for reproducibility

# All observers like the non-filtered equally
filterNon2 <- sample(high, trials*obs, replace = T)
# Half observers dislike one filter particularly
filterBad2 <- sample(low, trials*(obs/2), replace = T)
# Rest of observers dislike filters equally
filterMed2 <- sample(med, trials*(obs*1.5), replace = T)

# Create data frame for exp 2
ratings <- c(filterNon2,filterBad2,filterMed2)
results2 <- data.frame(ratings,filter,id)
results2$rating <- ordered(results2$ratings)


# Model Exp 2
# How to compare with Exp 1?