Abstract This study focused on how early misfit affected the recovery of θ for a computerized adaptive test (CAT). Number of misfitting items, generating θ, item selection method, and θ estimation method were independent variables in a monte-carlo simulation. It was found that CAT could recover from misfit-ascorrect-responses for low ability simulees given a sufficient number of items. CAT could not recover from misfit-as-incorrect-responses for high ability simulees. Implications of the study and suggestions for future research are provided
Item scores that do not fit an assumed item response theory model may cause the latent trait value t...
none2siThe paper deals with the introduction of empirical prior information in the estimation of can...
A new procedure, CATSIB, for assessing differential item functioning (DIF) on computerized adaptive ...
One of the aims of a computerized adaptive test (CAT) is to construct an optimal test for each exami...
The advantages that computer adaptive testing offers over linear tests have been well documented. Th...
This study utilizes an idea set forth by Matteucci and Veldkamp (2012) in which empirical prior dist...
Recent developments of person-fit analysis in computerized adaptive testing (CAT) are discussed. Met...
In this study we discuss recent developments of person-fit analysis in the context of computerized a...
A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimat...
The use of empirical prior information about participants has been shown to substantially improve th...
Item response theory (IRT) has been adapted as the theoretical foundation of computerized adaptive t...
Monte Carlo simulaition was used to investigate score bias'and information characteristics of O...
The paper deals with the introduction of empirical prior information in the estimation of candidate’...
Several person-fit statistics have been proposed to detect item score patterns that do not fit an it...
Abstract: A computerized adaptive testing (CAT) algorithm that has the potential to increase the ho...
Item scores that do not fit an assumed item response theory model may cause the latent trait value t...
none2siThe paper deals with the introduction of empirical prior information in the estimation of can...
A new procedure, CATSIB, for assessing differential item functioning (DIF) on computerized adaptive ...
One of the aims of a computerized adaptive test (CAT) is to construct an optimal test for each exami...
The advantages that computer adaptive testing offers over linear tests have been well documented. Th...
This study utilizes an idea set forth by Matteucci and Veldkamp (2012) in which empirical prior dist...
Recent developments of person-fit analysis in computerized adaptive testing (CAT) are discussed. Met...
In this study we discuss recent developments of person-fit analysis in the context of computerized a...
A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimat...
The use of empirical prior information about participants has been shown to substantially improve th...
Item response theory (IRT) has been adapted as the theoretical foundation of computerized adaptive t...
Monte Carlo simulaition was used to investigate score bias'and information characteristics of O...
The paper deals with the introduction of empirical prior information in the estimation of candidate’...
Several person-fit statistics have been proposed to detect item score patterns that do not fit an it...
Abstract: A computerized adaptive testing (CAT) algorithm that has the potential to increase the ho...
Item scores that do not fit an assumed item response theory model may cause the latent trait value t...
none2siThe paper deals with the introduction of empirical prior information in the estimation of can...
A new procedure, CATSIB, for assessing differential item functioning (DIF) on computerized adaptive ...