This article reviews a new item response theory (IRT) model estimation program, IRTPRO 2.1, for Windows that is capable of unidimensional and multidimensional IRT model estimation for existing and user-specified constrained IRT models for dichotomously and polytomously scored item response data.
CaiL. (2008). SEM of another flavour: Two new applications of the supplemented EM algorithm. British Journal of Mathematical and Statistical Psychology, 61, 309-329.
4.
CaiL. (2010a). High-dimensional exploratory item factor analysis by a Metropolis–Hasings Robbins–Monro algorithm. Psychometrika, 75, 33-57.
5.
CaiL. (2010b). Metropolis–Hastings Robbins–Monro algorithm for confirmatory item factor analysis. Journal of Educational and Behavioral Statistics, 35, 307-335.
6.
CaiL. (2010c). A two-tier full-information item factor analysis model with applications. Psychometrika, 75, 581-612.
7.
CaiL. (2011, July). Lord–Wingersky Algorithm After 25+ Years: Version 2.0 for hierarchical item factor models. Paper presented at the International Meeting of the Psychometric Society, Hong Kong, China.
8.
CaiL.ThissenD.du ToitS. H. C. (2011). IRTPRO for Windows [Computer software]. Lincolnwood, IL: Scientific Software International.
ChenW.-H.ThissenD. (1997). Local dependence indices for item pairs using response theory. Journal of Educational and Behavioral Statistics, 22, 265-289.
11.
FraserC.McDonaldR. P. (1988). NOHARM: Least squares item factor analysis. Multivariate Behavioral Research, 23, 267-269.
12.
LinacreJ. M. (2011). Winsteps® Rasch measurement computer program. Beaverton, OR. Available from Winsteps.com
13.
Maydeu-OlivaresA.JoeH. (2005). Limited and full information estimation and testing in 2n contingency tables: A unified framework. Journal of the American Statistical Association, 100, 1009-1020.
14.
Maydeu-OlivaresA.JoeH. (2006). Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika, 71, 713-732.
15.
MurakiE.BockR. D. (2003). PARSCALE 4: IRT item analysis and test scoring for rating-scale data [Computer software]. Chicago, IL: Scientific Software International.
16.
MuthénL.MuthénB. (2006). Mplus [Computer software]. Los Angeles, CA: Author.
17.
OrlandoM.ThissenD. (2000). Likelihood-based item fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24, 50-64.
18.
SchillingS.BockR. D. (2005). High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature. Psychometrika, 70, 533-555.
19.
ThissenD. (2003). MULTILOG 7: Multiple categorical item analysis and test scoring using item response theory [Computer software]. Chicago, IL: Scientific Software International.
20.
ThissenD.CaiL.BockR. D. (2010). The nominal item response model. In NeringM.OstiniR. (Eds.), Handbook of polytomous item response theory models (pp. 43-75). New York, NY: Routledge.
21.
ThissenD.NelsonL.RosaK.McLeodL. D. (2001). Item response theory for items scored in more than two categories. In ThissenD.WainerH. (Eds.), Test scoring (pp. 141-186). Mahwah, NJ: Erlbaum.
22.
ThissenD.SteinbergL. (1986). A taxonomy of item response models. Psychometrika, 51, 567-577.
23.
WuM.L.AdamsR. J.WilsonM. R. (1998). ConQuest: Generalized item response modeling software [Computer program]. Camberwell, Australia: Australian Council for Educational Research.