discrpar

0th

Percentile

Extract Discrimination Parameters of Item Response Models

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

Keywords
classes
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 plmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, …)
  # S3 method for gpcmodel
discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, …)
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 (plmodels 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.

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).

See Also

personpar, itempar, threshpar, guesspar, upperpar

Aliases
  • discrpar
  • discrpar.raschmodel
  • discrpar.rsmodel
  • discrpar.pcmodel
  • discrpar.plmodel
  • discrpar.gpcmodel
  • coef.discrpar
  • print.discrpar
  • vcov.discrpar
Examples
# NOT RUN {
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 <- plmodel(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)
# }
Documentation reproduced from package psychotools, version 0.5-1, License: GPL-2 | GPL-3

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