Residuals in an IRT Model
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_{pi} |
X_var |
Variance of the item response X_{pi} |
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.
############################################################################# # 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)
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