Three person-fit indexes with estimated ability level: a simulation study

Conference (2010, April)

An iterative maximum a posteriori estimation of proficiency level to detect multiple local likelihood maxima

in Applied Psychological Measurement (2010), 34

In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The ... [more ▼]

In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its use. The authors then propose an iteratively based MAP estimator (IMAP), which can be useful in detecting multiple local likelihood maxima. The efficiency of the IMAP estimator is studied and is compared to the ML and MAP methods by means of a simulation study. [less ▲]

Présentation d’un outil logiciel pour soutenir la détection des tentatives de fraudes lors de l’évaluation des apprentissages

Conference (2009, November)

Multidimensional fluctuation, pseudo-guessing and carelness IRT person parameters models

Conference (2009, July)

Comparaison empirique des méthodes classiques de détection du fonctionnement différentiel d’items en psychométrie

Conference (2009, May)

La correction du résultat d’un étudiant en présence de tentatives de fraudes

Scientific conference (2009, January)

Multidimensional item response theory models integrating additional inattention, pseudo-guessing, and discrimination person parameters

Conference (2008, June)

Est-ce qu'il est possible d'obtenir le résultat véritable d'un élève même si celui-ci tente de tricher ?

Conference (2007, October)

Adaptive estimators of trait level in adaptive testing: Some proposals

in Weiss, David (Ed.) Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing (2007, June)

In a computerized adaptive test (CAT), we seek an acceptably accurate trait (θ) level estimate using an optimal number of items. Bayesian estimation methods like MAP and EAP are often used to compute that ... [more ▼]

In a computerized adaptive test (CAT), we seek an acceptably accurate trait (θ) level estimate using an optimal number of items. Bayesian estimation methods like MAP and EAP are often used to compute that estimate. Unfortunately, with such methods, decreasing the number of items generates bias whenever the true θ level differs significantly from the a priori estimate. Adaptive versions of the maximum a posteriori and expected a posteriori estimation methods are proposed to reduce this bias. These AMAP and AEAP methods adapt the a priori values used in the estimation function according to the previously computed θ estimate obtained from the previous administered item. The performance of AMAP and AEAP is evaluated in a CAT context. [less ▲]

Sur l'utilisation de la variabilité de sujet pour corriger l'habileté: méthode et premiers résultats

Scientific conference (2006, November)