The use of predicted values for item parameters in item response theory models: an application in intelligence tests

References

• Albert , J. H. 1992 . Bayesian estimation of normal ogive item response curves using Gibbs sampling . J. Educ. Stat. , 17 : 251 – 269 . (doi:10.2307/1165149)
   Google Scholar
• Ariel , A. , Veldkamp , B. P. and Breithaupt , K. 2006 . Optimal testlet pool assembly for multi-stage testing designs . Appl. Psych. Meas. , 30 : 204 – 215 . (doi:10.1177/0146621605284350)
   Web of Science ®Google Scholar
• Béguin , A. A. and Glas , C. A.W. 2001 . MCMC estimation and some model-fit analysis of multidimensional IRT models . Psychometrika , 66 : 541 – 562 . (doi:10.1007/BF02296195)
   Web of Science ®Google Scholar
• Birnbaum , A. 1968 . “ Some latent trait models and their use in inferring an examinee's ability ” . In Statistical Theories of Mental Test Scores , Edited by: Lord , F. M. and Novick , M. R. 397 – 479 . Addison-Wesley, Reading .
   Google Scholar
• Bock , R. D. and Aitkin , M. 1981 . Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm . Psychometrika , 46 : 443 – 459 . (doi:10.1007/BF02293801)
   Web of Science ®Google Scholar
• Bolt , D. M. and Lall , V. F. 2003 . Estimation of compensatory and noncompensatory multidimensional item response models using Markov chain Monte Carlo . Appl. Psych. Meas. , 27 : 395 – 414 . (doi:10.1177/0146621603258350)
   Web of Science ®Google Scholar
• Bousquet , N. 2008 . Diagnostics of prior-data agreement in applied Bayesian analysis . J. Appl. Stat. , 35 : 1011 – 1029 . (doi:10.1080/02664760802192981)
   Web of Science ®Google Scholar
• Breiman , L. , Friedman , J. H. , Olshen , R. A. and Stone , C. J. 1984 . Classification and Regression Trees , Belmont : Wadsworth International .
   Google Scholar
• Cowles , M. K. and Carlin , B. P. 1996 . Markov chain Monte Carlo convergence diagnostics: A comparative review . J. Amer. Statist. Assoc. , 91 : 883 – 904 . (doi:10.1080/01621459.1996.10476956)
   Web of Science ®Google Scholar
• De'ath , G. 2002 . Multivariate regression trees: A new technique for modeling species–environment relationships . Ecology , 83 : 1105 – 1117 .
   Web of Science ®Google Scholar
• De Ayala , R. J. 2009 . The Theory and Practice of Item Response Theory , New York : The Guilford Press .
   Google Scholar
• De Gruijter , D. N.M. and van der Kamp , L. J.T. 2008 . Statistical Test Theory for the Behavioral Sciences , Boca Raton , FL : Chapman & Hall/CRC .
   Google Scholar
• Enright , M. K. and Sheehan , K. M. 2002 . “ Modeling the difficulty of quantitative reasoning items: Implication for item generation ” . In Item Generation for Test Development , Edited by: Irvine , S. H. and Kyllonen , P. C. 129 – 158 . Mahwah , NJ : Lawrence Erlbaum Associates .
   Google Scholar
• Fox , J. P. and Glas , C. A.W. 2001 . Bayesian estimation of a multilevel IRT model using Gibbs sampling . Psychometrika , 66 : 271 – 288 . (doi:10.1007/BF02294839)
   Web of Science ®Google Scholar
• Gelman , A. 2002 . “ Prior distribution ” . In Encyclopedia of Environmetrics , Edited by: El-Shaarawi , A. H. and Piegorsch , W. W. 1634 – 1637 . Chichester : John Wiley & Sons .
   Google Scholar
• Geman , S. and Geman , D. 1984 . Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images . IEEE Trans. Pattern Anal. Mach. Intell. , 6 : 721 – 741 . (doi:10.1109/TPAMI.1984.4767596)
   PubMed Web of Science ®Google Scholar
• Geweke , J. 1992 . “ Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments ” . In Bayesian Statistics 4 , Edited by: Bernardo , J. M. , Berger , J. , Dawid , A. P. and Smith , A. F.M. 169 – 193 . Oxford : Oxford University Press .
   Google Scholar
• Haley , D. C. 1952 . Estimation of the dosage mortality relationship when the dose is subject to error , Stanford : Stanford University, Applied Mathematics and Statistics Laboratory . Tech. Rep. N. 15
   Google Scholar
• Hambleton , R. K. and Swaminathan , H. 1985 . Item Response Theory: Principles And Applications , Boston , MA : Kluwer Nijhoff Publishing .
   Google Scholar
• Larsen , D. R. and Speckman , P. L. 2004 . Multivariate regression trees for analysis of abundance data . Biometrics , 60 : 543 – 549 . (doi:10.1111/j.0006-341X.2004.00202.x)
   PubMed Web of Science ®Google Scholar
• van der Kleij , F. M. , Eggen , T. J.H.M. , Timmers , C. F. and Veldkamp , B. P. 2012 . Effects of feedback in a computer-based assessment for learning . Comput. Educ. , 58 : 263 – 272 . (doi:10.1016/j.compedu.2011.07.020)
   Web of Science ®Google Scholar
• van der Linden , W. J. 1999 . Empirical initialization of the trait estimation in adaptive testing . Appl. Psych. Meas. , 23 : 21 – 29 . (doi:10.1177/01466219922031149)
   Web of Science ®Google Scholar
• van der Linden , W. J. and Glas , C. A.W. 2010 . Elements of Adaptive Testing , New York : Springer-Verlag .
   Google Scholar
• van der Linden , W. J. and Hambleton , R. K. 1997 . Handbook of Modern Item Response Theory , New York : Springer-Verlag .
   Google Scholar
• van der Linden , W. J. and Pashley , P. J. 2010 . “ Item selection and ability estimation in adaptive testing ” . In Elements of Adaptive Testing , Edited by: van der Linden , W. J. and Glas , C. A.W. 3 – 30 . New York : Springer .
   Google Scholar
• Lord , F. M. 1952 . A theory of test scores . Psychometric Monogr. , 7 : 1 – 84 .
   Google Scholar
• Lord , F. M. and Novick , M. R. 1968 . Statistical Theories of Mental Test Scores , Reading , MA : Addison-Wesley .
   Google Scholar
• Maij-de Meij , A. M. , Schakel , L. , Smid , N. , Verstappen , N. and Jaganjac , A. 2008 . Connector Ability, Professional Manual , Utrecht : Pi Company B.V .
   Google Scholar
• Makransky , G. and Glas , C. A.W. 2010 . An automatic online calibration design in adaptive testing . J. Appl. Test. Technol. , 11 : 1 – 29 .
   Google Scholar
• Matteucci , M. and Veldkamp , B. P. 2011 . “ Including empirical prior information in test administration ” . In Classification and Multivariate Analysis for Complex Data Structures , Edited by: Fichet , B. , Piccolo , D. , Verde , R. and Vichi , M. 173 – 181 . Berlin, Heidelberg : Springer-Verlag .
   Google Scholar
• Matteucci , M. , Mignani , S. and Veldkamp , B. P. 2009 . “ Issues on item response theory modeling ” . In Statistical Methods for the Evaluation of Educational Services and Quality of Products , Edited by: Bini , M. , Monari , P. , Piccolo , D. and Salmaso , L. 29 – 45 . Berlin, Heidelberg : Springer-Verlag .
   Google Scholar
• Matteucci , M. , Mignani , S. and Veldkamp , B. P. 2012 . Prior distributions for item parameters in IRT models . Commun. Stat. Theory Methods. , 41 : 2944 – 2958 . (doi:10.1080/03610926.2011.639973)
   Web of Science ®Google Scholar
• OECD . 2010 . PISA 2009 Results: Overcoming Social Background – Equity in Learning, Opportunities and Outcomes (Volume II) Available at http://dx.doi.org/10.1787/9789264091504-en.
   Google Scholar
• Patz , R. J. and Junker , B. W. 1999 . A straightforward approach to Markov chain Monte Carlo methods for item response models . J. Educ. Behav. Stat. , 24 : 146 – 178 .
   Web of Science ®Google Scholar
• Segal , M. R. 1992 . Tree-structured methods for longitudinal data . J. Amer. Statist. Assoc. , 87 : 407 – 418 . (doi:10.1080/01621459.1992.10475220)
   Web of Science ®Google Scholar
• Smith , B. J. 2007 . Boa: An R package for MCMC output convergence assessment and posterior inference . J. Stat. Softw. , 21 : 1 – 37 .
   Web of Science ®Google Scholar
• The MathWorks Inc . 2005 . MATLAB 7.1 Natick , MA
   Google Scholar
• Tsutakawa , R. K. 1992 . Prior distribution for item response curves . Br. J. Math. Stat. Psych. , 45 : 51 – 74 . (doi:10.1111/j.2044-8317.1992.tb00977.x)
   Web of Science ®Google Scholar
• Veldkamp , B. P. 2012 . “ Ensuring the future of CAT ” . In Psychometrics in Practice at RCEC Edited by: Eggen , T. J.H.M. and Veldkamp , B. P. 35 – 46 . Available at: http://dx.doi.org/10.3990/3.9789036533744.ch4.
   Google Scholar
• Veldkamp , B. P. , Matteucci , M. and de Jong , M. 2012 . “ Uncertainties in the item parameter estimates and robust automated test assembly ” . submitted for publication. Available at http://amsacta.unibo.it/3240/.
   Google Scholar
• Wright , D. 2002 . “ Scoring tests when items have been generated ” . In Item Generation for Test Development , Edited by: Irvine , S. H. and Kyllonen , P. C. 277 – 286 . Mahwah, NJ : Lawrence Erlbaum Associates .
   Google Scholar
• Zwinderman , A. H. 1997 . “ Response models with manifest predictors ” . In Handbook of Modern Item Response Theory , Edited by: van der Linden , W. J. and Hambleton , R. K. 245 – 256 . New York : Springer-Verlag .
   Google Scholar