IRT.residuals {TAM} | R Documentation |
Residuals in an IRT Model
Description
Defines an S3 method for the computation of observed residual values.
The computation of residuals is based on weighted likelihood estimates as
person parameters, see tam.wle
.
IRT.residuals
can only be applied for unidimensional IRT models.
The methods IRT.residuals
and residuals
are equivalent.
Usage
IRT.residuals(object, ...)
## S3 method for class 'tam.mml'
IRT.residuals(object, ...)
## S3 method for class 'tam.mml'
residuals(object, ...)
## S3 method for class 'tam.mml.2pl'
IRT.residuals(object, ...)
## S3 method for class 'tam.mml.2pl'
residuals(object, ...)
## S3 method for class 'tam.mml.mfr'
IRT.residuals(object, ...)
## S3 method for class 'tam.mml.mfr'
residuals(object, ...)
## S3 method for class 'tam.jml'
IRT.residuals(object, ...)
## S3 method for class 'tam.jml'
residuals(object, ...)
Arguments
object |
Object of class |
... |
Further arguments to be passed |
Value
List with following entries
residuals |
Residuals |
stand_residuals |
Standardized residuals |
X_exp |
Expected value of the item response |
X_var |
Variance of the item response |
theta |
Used person parameter estimate |
probs |
Expected item response probabilities |
Note
Residuals can be used to inspect local dependencies in the item response data, for example using principle component analysis or factor analysis (see Example 1).
See Also
See also the eRm::residuals
(eRm) or
residuals
(mirt)
functions.
See also predict.tam.mml
.
Examples
## Not run:
#############################################################################
# EXAMPLE 1: Residuals data.read
#############################################################################
library(sirt)
data(data.read, package="sirt")
dat <- data.read
# for Rasch model
mod <- TAM::tam.mml( dat )
# extract residuals
res <- TAM::IRT.residuals( mod )
str(res)
## End(Not run)