discrpar: Extract Discrimination Parameters of Item Response Models

Description

A class and generic function for representing and extracting the discrimination parameters of a given item response model.

Usage

discrpar(object, ...)
  # S3 method for raschmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)
  # S3 method for rsmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)
  # S3 method for pcmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)
  # S3 method for nplmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)
  # S3 method for gpcmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)

Value

A named vector with discrimination parameters of class discrpar and additional attributes model (the model name), ref (the items or parameters used as restriction/for normalization), alias (either

TRUE or a named numeric vector with the aliased parameters not included in the return value), and vcov (the estimated and adjusted variance-covariance matrix).

Arguments

object: a fitted model object whose discrimination parameters should be extracted.
ref: a restriction to be used. Not used for models estimated via CML as the discrimination parameters are fixed to 1 in raschmodels, rsmodels and pcmodels. For models estimated via MML (nplmodels and gpcmodels), the parameters are by default identified via the distributional parameters of the person parameters (mean and variance of a normal distribution). Nevertheless, a restriction on the ratio scale can be applied.
alias: logical. If TRUE (the default), the aliased parameters are included in the return vector (and in the variance-covariance matrix if vcov = TRUE). If FALSE, these parameters are removed. For raschmodels, rsmodels and pcmodels where all discrimination parameters are fixed to 1, this means that an empty numeric vector and an empty variance-covariance matrix is returned if alias is FALSE.
vcov: logical. If TRUE (the default), the variance-covariance matrix of the discrimination parameters is attached as attribute vcov.
...: further arguments which are currently not used.

Details

discrpar is both, a class to represent discrimination parameters of item response models as well as a generic function. The generic function can be used to extract the discrimination parameters of a given item response model.

For objects of class discrpar, several methods to standard generic functions exist: print, coef, vcov. coef and vcov can be used to extract the discrimination parameters and their variance-covariance matrix without additional attributes.

Examples

Run this code

o <- options(digits = 4)

## load verbal aggression data
data("VerbalAggression", package = "psychotools")

## fit Rasch model to verbal aggression data
rmod <- raschmodel(VerbalAggression$resp2)

## extract the discrimination parameters
dp1 <- discrpar(rmod)

## extract the standard errors
sqrt(diag(vcov(dp1)))

if(requireNamespace("mirt")) {
## fit 2PL to verbal aggression data
twoplmod <- nplmodel(VerbalAggression$resp2)

## extract the discrimination parameters
dp2 <- discrpar(twoplmod)

## this time with the first discrimination parameter being the reference
discrpar(twoplmod, ref = 1)

## extract the standard errors
sqrt(diag(vcov(dp2)))
}

options(digits = o$digits)