## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE, comment = "#>",
  fig.width = 7, fig.height = 4.2, dpi = 96
)
options(digits = 4)

## ----library------------------------------------------------------------------
library(rasch)

## ----baseline-data------------------------------------------------------------
d <- simulate_rasch(n_persons = 400, n_items = 10, seed = 101)
names(attr(d, "truth"))

## ----baseline-----------------------------------------------------------------
fit <- rasch(d, id = "id")
rec <- sim_recovery(fit, d)
rec

## ----baseline-plot, fig.alt = "Planted and recovered item and person locations."----
plot_recovery(rec)

## ----discrim------------------------------------------------------------------
disc <- rep(1, 10)
disc[5] <- 2.5
disc[6] <- 0.4

d2 <- simulate_rasch(400, 10, discrimination = disc, seed = 21)
fit2 <- rasch(d2, id = "id")
fit2$items[, c("item", "location", "infit_ms", "outfit_ms")]

## ----dif----------------------------------------------------------------------
d3 <- simulate_rasch(
  500, 10,
  dif = list(items = "I06", uniform = 1),
  n_groups = 2,
  seed = 303
)

fit3 <- rasch(d3, id = "id", factors = "group")
da <- dif_anova(fit3)
da$summary[, c("item", "term", "F_uniform", "p_uniform_adj", "uniform_DIF")]

## ----dif-size-----------------------------------------------------------------
dif_size(fit3, "I06", by = "group")

## ----dependence---------------------------------------------------------------
d4 <- simulate_rasch(
  500, 10,
  dependence = list(
    pairs = list(c("I04", "I05")),
    strength = 1.8
  ),
  seed = 41
)

fit4 <- rasch(d4, id = "id")
rc <- residual_correlations(fit4, flag = 0.20)
head(rc$pairs, 3)

## ----dependence-size----------------------------------------------------------
dependence_magnitude(fit4, dependent = "I05", independent = "I04")

## ----btl----------------------------------------------------------------------
b <- simulate_btl(
  n_objects = 7,
  n_judges = 8,
  reps_per_pair = 30,
  erratic_judges = 0.25,
  seed = 61
)

bt <- btl(b, "object_a", "object_b", winner = "winner", judge = "judge")
bt$judges[order(-bt$judges$fit_resid), ]

## ----transitivity-------------------------------------------------------------
tr <- btl_transitivity(bt)
tr$summary
head(tr$judges)

## ----power--------------------------------------------------------------------
batch <- sim_replicate(
  simulate_rasch, 10,
  n_persons = 400,
  n_items = 8,
  dif = list(items = "I04", uniform = 0.8),
  n_groups = 2,
  seed = 700
)

flagged <- vapply(batch, function(dd) {
  s <- dif_anova(rasch(dd, id = "id", factors = "group"))$summary
  isTRUE(s$uniform_DIF[s$item == "I04"])
}, logical(1))

mean(flagged)