psychotools (version 0.4-2)

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, …)

Arguments

object

a fitted model object whose discrimination parameters should be extracted.

ref

a restriction to be used to ensure parameter identifiability of the item discrimination parameters. Currently not used as the item discrimination parameters are fixed to unity in raschmodel's, rsmodel's and pcmodel's.

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 raschmodel's, rsmodel's and pcmodel's where all item discrimination parameters are fixed to unity, this means that an empty numeric vector and an empty variance-covariace 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.

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).

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.

See Also

personpar, itempar, threshpar

Examples

# NOT RUN {
## load verbal aggression data
data("VerbalAggression", package = "psychotools")

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

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

## extract the variance-covariance matrix
head(vcov(dp))
# }