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

## ----setup--------------------------------------------------------------------
library(intraclass)

## ----dstudy, eval = requireNamespace("glmmTMB", quietly = TRUE)---------------
fit <- icc(ratings, score, subject, rater, type = "agreement", seed = 1)
proj <- d_study(fit, m = 1:8, seed = 1)
proj

## ----dstudy-tidy, eval = requireNamespace("glmmTMB", quietly = TRUE)----------
tidy(proj)

glance(proj)

## ----dstudy-plot, eval = requireNamespace("ggplot2", quietly = TRUE) && requireNamespace("glmmTMB", quietly = TRUE), fig.alt = "Projected reliability rising with the number of raters, with a Monte-Carlo interval band."----
library(ggplot2)
autoplot(d_study(fit, m = 1:12))

## ----dstudy-plot-wrapper, eval = FALSE----------------------------------------
# plot(proj)

## ----dstudy-unit, eval = requireNamespace("glmmTMB", quietly = TRUE)----------
icc(ratings, score, subject, rater,
  type = "agreement", unit = c("single", "average", 6), seed = 1
)

## ----dstudy-unit-fixed, error = TRUE, eval = requireNamespace("glmmTMB", quietly = TRUE)----
try({
icc(ratings, score, subject, rater,
  type = "agreement", raters = "fixed", unit = c("single", "average", 6),
  seed = 1
)
})

## ----replicates-data, eval = requireNamespace("glmmTMB", quietly = TRUE)------
set.seed(2025)
ns <- 20
nr <- 4
no <- 3
grid <- expand.grid(subject = seq_len(ns), rater = seq_len(nr), occ = seq_len(no))
subj <- rnorm(ns, sd = 1.1)[grid$subject]
rater <- rnorm(nr, sd = 0.8)[grid$rater]
sr <- rnorm(ns * nr, sd = 0.6)[(grid$rater - 1) * ns + grid$subject]
reps <- data.frame(
  subject = factor(grid$subject),
  rater = factor(grid$rater),
  score = 10 + subj + rater + sr + rnorm(nrow(grid), sd = 0.7)
)

icc(reps, score, subject, rater, type = "agreement", occasions = c("single", "average"))

## ----occasion-dstudy, eval = requireNamespace("glmmTMB", quietly = TRUE)------
fit_rep <- icc(reps, score, subject, rater, type = "agreement", occasions = "average")
d_study(fit_rep, n_o = 1:6)

## ----plot-coef, eval = requireNamespace("ggplot2", quietly = TRUE) && requireNamespace("glmmTMB", quietly = TRUE), fig.alt = "Forest plot of ICC(A,1) and ICC(A,k) for the ratings data, each a point estimate with a horizontal Monte-Carlo interval, ICC(A,k) higher than ICC(A,1), and its interval slightly wider."----
library(ggplot2)
autoplot(fit) # `fit <- icc(ratings, score, subject, rater, type = "agreement", seed = 1)`

## ----plot-comp, eval = requireNamespace("ggplot2", quietly = TRUE) && requireNamespace("glmmTMB", quietly = TRUE), fig.alt = "Bar chart of the estimated variance components for the ratings fit: subject, rater, and residual, with the rater component the largest."----
autoplot(fit, what = "components")