Compute a Crosswalk Table

Source: R/core_functions.R

getRSSS is a function for generating a raw-score to standard-score crosswalk table.

getRSSS(ipar, model_id, theta_grid, is_minscore_0, prior_mu_sigma)

Arguments

ipar

an item parameter matrix for graded response items. Accepts both a/b and a/d format parameters. Accepts multidimensional item parameters.

model_id

the column name for item models.

theta_grid

the theta grid to use for numerical integration.

is_minscore_0

if TRUE, the score of each item begins from 0. if FALSE, the score of each item begins from 1.

prior_mu_sigma

a named list containing prior distribution parameters. All values must be in the theta metric.

  • mu the prior means

  • sigma the covariance matrix

  • sd the prior standard deviations

  • corr the correlation matrix

Examples

# \donttest{
## Free calibration without using anchor

o <- runCalibration(data_asq, technical = list(NCYCLES = 1000))

ipar <- mirt::coef(o, IRTpars = TRUE, simplify = TRUE)$items
ipar <- as.data.frame(ipar)
ipar[, data_asq@model_id] <- data_asq@itemmap[, data_asq@model_id]
items <- getItemNames(data_asq, 2)

getRSSS(
  ipar = ipar[items, ],
  model_id = data_asq@model_id,
  theta_grid = seq(-4, 4, .1),
  is_minscore_0 = TRUE,
  prior_mu_sigma = list(mu = 0, sigma = 1)
)
# }