IRT.residuals | R Documentation |
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.
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, ...)
object |
Object of class |
... |
Further arguments to be passed |
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 |
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 the eRm::residuals
(eRm) or
residuals
(mirt)
functions.
See also predict.tam.mml
.
## 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)
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