getRSSS: Compute a Crosswalk Table

In choi-phd/PROsetta: Linking Patient-Reported Outcomes Measures

Compute a Crosswalk Table

Description

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

Usage

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

## 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)
)

choi-phd/PROsetta documentation built on Nov. 27, 2024, 5:45 a.m.