## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(cdCAT)

## ----items--------------------------------------------------------------------
# Q-matrix: 5 items, 2 attributes
Q <- matrix(c(
  1, 0,
  0, 1,
  1, 0,
  0, 1,
  1, 1
), nrow = 5, ncol = 2, byrow = TRUE)

# DINA model parameters
items <- cdcat_items(
  q_matrix = Q,
  model    = "DINA",
  slip     = c(0.10, 0.10, 0.15, 0.10, 0.10),
  guess    = c(0.20, 0.20, 0.15, 0.20, 0.15)
)

print(items)

## ----session------------------------------------------------------------------
# Start session
session <- CdcatSession$new(
  items     = items,
  method    = "MAP",
  criterion = "PWKL",
  min_items = 2L,
  max_items = 5L,
  threshold = 0.8
)

# Simulate responses (1 = correct, 0 = incorrect)
simulated_responses <- c(1, 1, 0, 1, 0)

repeat {
  item <- session$next_item()
  if (item == 0) break
  session$update(item, simulated_responses[item])
}

## ----results------------------------------------------------------------------
res <- session$result()

cat("Estimated profile :", res$alpha_hat, "\n")
cat("Items administered:", res$administered, "\n")
cat("Responses         :", res$responses, "\n")
cat("N items           :", res$n_items, "\n")
cat("Stop reason       :", res$stop_reason, "\n")
cat("Posterior         :", round(res$posterior, 3), "\n")

## ----models, eval=FALSE-------------------------------------------------------
# # DINO model
# items_dino <- cdcat_items(Q, "DINO", slip = slip, guess = guess)
# 
# # GDINA model
# gdina_params <- list(
#   list("0" = 0.1, "1" = 0.9),
#   list("0" = 0.1, "1" = 0.9),
#   list("00" = 0.1, "10" = 0.5, "01" = 0.5, "11" = 0.9)
# )
# items_gdina <- cdcat_items(Q[1:3, ], "GDINA", gdina_params = gdina_params)