gen_data: Generate item response data sets
In haziqj/diagacc: Modelling Diagnostic Accuracy using Latent Class Models

Description Usage Arguments Details Value Author(s)

Generate a data set using the simple latent class model (gen_lc), the latent class with random effects model (gen_lcre), or the finite mixture model (gen_fm) as the underlying data generating mechanism.

gen_lc(
  n = 250,
  tau = 0.08,
  miss.prop = 0.2,
  seed = NULL,
  name.items = TRUE,
  drop.gs = FALSE
)

gen_lcre(
  n = 250,
  tau = 0.08,
  miss.prop = 0.2,
  seed = NULL,
  sigma = c(1.5, 1.5),
  name.items = TRUE,
  drop.gs = FALSE
)

gen_fm(
  n = 250,
  tau = 0.08,
  miss.prop = 0.2,
  seed = NULL,
  eta = c(0.5, 0.2),
  name.items = TRUE,
  drop.gs = FALSE
)

`n`	Sample size.
`tau`	Prevalence of the disease, i.e. P(δ=1).
`miss.prop`	Proportion of missing values in the gold standard item.
`seed`	Random seed.
`name.items`	(Logical) Use item names as set in the options?
`drop.gs`	(Logical) Drop the gold standard item?
`sigma`	The standard deviation of the random effects.
`eta`	(Vector of length 2) Probabilities of correctly classifying diseased and healthy individuals respectively.