%0 Journal Article %J Journal of Applied Measurement %D 2009 %T a posteriori estimation in adaptive testing: Adaptive a priori, adaptive correction for bias, and adaptive integration interval %A Raîche, G. %A Blais, J-G. %B Journal of Applied Measurement %V 10(2) %G eng %0 Book Section %D 2007 %T Partial order knowledge structures for CAT applications %A Desmarais, M. C. %A Pu, X, %A Blais, J-G. %C D. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing. %G eng %0 Journal Article %J Applied Psychological Measurement %D 2006 %T SIMCAT 1.0: A SAS computer program for simulating computer adaptive testing %A Raîche, G. %A Blais, J-G. %K computer adaptive testing %K computer program %K estimated proficiency level %K Monte Carlo methodologies %K Rasch logistic model %X Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their flexibility is limited. SIMCAT 1.0 is aimed at the simulation of adaptive testing sessions under different adaptive expected a posteriori (EAP) proficiency-level estimation methods (Blais & Raîche, 2005; Raîche & Blais, 2005) based on the one-parameter Rasch logistic model. These methods are all adaptive in the a priori proficiency-level estimation, the proficiency-level estimation bias correction, the integration interval, or a combination of these factors. The use of these adaptive EAP estimation methods diminishes considerably the shrinking, and therefore biasing, effect of the estimated a priori proficiency level encountered when this a priori is fixed at a constant value independently of the computed previous value of the proficiency level. SIMCAT 1.0 also computes empirical and estimated skewness and kurtosis coefficients, such as the standard error, of the estimated proficiency-level sampling distribution. In this way, the program allows one to compare empirical and estimated properties of the estimated proficiency-level sampling distribution under different variations of the EAP estimation method: standard error and bias, like the skewness and kurtosis coefficients. (PsycINFO Database Record (c) 2007 APA, all rights reserved) %B Applied Psychological Measurement %I Sage Publications: US %V 30 %P 60-61 %@ 0146-6216 (Print) %G eng %M 2005-16359-005 %0 Book Section %D 2005 %T Features of the estimated sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules %A Blais, J-G. %A Raîche, G. %C D. G. Englehard (Eds.), Objective measurement: Theory into practice. Volume 6. %G eng %0 Journal Article %J Mesure et évaluation en éducation %D 2002 %T Étude de la distribution d'échantillonnage de l'estimateur du niveau d'habileté en testing adaptatif en fonction de deux règles d'arrêt dans le contexte de l'application du modèle de Rasch [Study of the sampling distribution of the proficiecy estima %A Raîche, G. %A Blais, J-G. %B Mesure et évaluation en éducation %V 24(2-3) %P 23-40 %G French %0 Conference Paper %B Paper presented at the annual meeting of the International Objective Measurement Workshops-XI %D 2002 %T Some features of the sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules %A Blais, J-G. %A Raiche, G. %B Paper presented at the annual meeting of the International Objective Measurement Workshops-XI %C New Orleans, LA %G eng