MAT-package | R Documentation |
MAT is a package to simulate Multidimensional Adaptive Testing (MAT) for the Multidimensional 3-Parameter Logistic (M3PL) Model as described in Segall (1996), Reckase (2009), and Mulder & van der Linden (2009).
Package: | MAT |
Type: | Package |
Version: | 2.0 |
Date: | 2011-01-25 |
License: | GPL |
LazyLoad: | yes |
Seung W. Choi and David R. King
Maintainer: Seung W. Choi <s-choi@northwestern.edu>
Choi, S. W., & King, D. R. (2015). R Package MAT: Simulation of multidimensional adaptive testing for dichotomous IRT models. Applied Psychological Measurement, 39(3), 239-240.
Segall, D. O. (1996). Multidimensional adaptive testing, Psychometrika, 61(2), 331-354
van der Linden, W. J. (1999). Multidimensional adaptive testing with a minimum error-variance criterion, Journal of Educational and Behavioral Statistics, 24(4), 398-412.
Mulder, J., & van der Linden, W. J. (2009). Multidimensional adaptive testing with optimal design criteria for item selection, Psychometrika, 74(2), 273-296.
Reckase, M. D. (2009). Multidimensional Item Response Theory. New York: Springer.
#load sample item parameters containing 180 items measuring three dimensions data(sample.ipar) #create a variance-covariance (correlation) matrix vcv1<-diag(3); vcv1[lower.tri(vcv1,diag=FALSE)]<-c(.5,.6,.7) #simulate item responses resp1<-simM3PL(sample.ipar, vcv1, 3, n.simulee = 100)$resp #specify target content distributions target.content.dist1<-c(1/3,1/3,1/3) #content category designations for items content.cat1<-rep(1:3,rep(60,3)) #simulate multidimensional adaptive testing MCAT.1<-MAT(sample.ipar, resp1, vcv1, target.content.dist=target.content.dist1, content.cat=content.cat1, ncc=3, p=3, selectionMethod="A", topN=1, selectionType="FISHER", stoppingCriterion="CONJUNCTIVE", minNI=10, maxNI=30)
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