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.
discrpar(object, ...) ## S3 method for class 'raschmodel' discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...) ## S3 method for class 'rsmodel' discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...) ## S3 method for class 'pcmodel' discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...) ## S3 method for class 'plmodel' discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...) ## S3 method for class 'gpcmodel' discrpar(object, ref = NULL, alias = TRUE, vcov = TRUE, ...)
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 |
alias |
logical. If |
vcov |
logical. If |
... |
further arguments which are currently not used. |
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.
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).
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)
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