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Volumn 75, Issue 3, 2010, Pages 474-497

A Markov chain Monte Carlo approach to confirmatory item factor analysis

Author keywords

item factor analysis; Markov chain Monte Carlo; multidimensional item response theory

Indexed keywords


EID: 77956060011     PISSN: 00333123     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11336-010-9161-9     Document Type: Article
Times cited : (71)

References (71)
  • 1
    • 0031512887 scopus 로고    scopus 로고
    • The multidimensional random coefficients multinomial logit model
    • Adams, R. J., Wilson, M., & Wang, W. (1997). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurement, 21, 1-23.
    • (1997) Applied Psychological Measurement , vol.21 , pp. 1-23
    • Adams, R.J.1    Wilson, M.2    Wang, W.3
  • 2
    • 0001248506 scopus 로고
    • Bayesian estimation of normal ogive item response curves using Gibbs sampling
    • Albert, J. H. (1992). Bayesian estimation of normal ogive item response curves using Gibbs sampling. Journal of Educational Statistics, 17, 251-269.
    • (1992) Journal of Educational Statistics , vol.17 , pp. 251-269
    • Albert, J.H.1
  • 4
    • 0035543525 scopus 로고    scopus 로고
    • MCMC estimation and some model-fit analysis of multidimensional IRT models
    • Béguin, A. A., & Glas, C. A. W. (2001). MCMC estimation and some model-fit analysis of multidimensional IRT models. Psychometrika, 66, 541-561.
    • (2001) Psychometrika , vol.66 , pp. 541-561
    • Béguin, A.A.1    Glas, C.A.W.2
  • 6
    • 0000433590 scopus 로고
    • Marginal maximum likelihood estimation of item parameters: An application of the EM algorithm
    • Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: An application of the EM algorithm. Psychometrika, 46, 443-459.
    • (1981) Psychometrika , vol.46 , pp. 443-459
    • Bock, R.D.1    Aitkin, M.2
  • 9
    • 0345149832 scopus 로고    scopus 로고
    • Estimation of compensatory and noncompensatory multidimensional IRT models using Markov chain Monte Carlo
    • Bolt, D. M., & Lall, V. F. (2003). Estimation of compensatory and noncompensatory multidimensional IRT models using Markov chain Monte Carlo. Applied Psychological Measurement, 27, 395-414.
    • (2003) Applied Psychological Measurement , vol.27 , pp. 395-414
    • Bolt, D.M.1    Lall, V.F.2
  • 10
    • 0033239554 scopus 로고    scopus 로고
    • A Bayesian random effects model for testlets
    • Bradlow, E. T., Wainer, H., & Wang, X. (1999). A Bayesian random effects model for testlets. Psychometrika, 64, 153-168.
    • (1999) Psychometrika , vol.64 , pp. 153-168
    • Bradlow, E.T.1    Wainer, H.2    Wang, X.3
  • 11
    • 77956059224 scopus 로고    scopus 로고
    • Cai, L. (In Press-a). High-dimensional exploratory item factor analysis by a Metropolis-Hastings Robbins-Monro algorithm. Psychometrika.
  • 12
    • 77956061769 scopus 로고    scopus 로고
    • Cai, L. (In Press-b). Metropolis-Hastings Robbins-Monro algorithm for confirmatory item factor analysis. Journal of Educational and Behavioral Statistics.
  • 16
    • 32344446687 scopus 로고
    • Understanding the Metropolis-Hastings algorithm
    • Chib, S., & Greenberg, E. (1995). Understanding the Metropolis-Hastings algorithm. The American Statistician, 49, 327-335.
    • (1995) The American Statistician , vol.49 , pp. 327-335
    • Chib, S.1    Greenberg, E.2
  • 17
    • 21344474305 scopus 로고    scopus 로고
    • Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models
    • Cowles, M. K. (1996). Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models. Statistics and Computing, 6, 101-111.
    • (1996) Statistics and Computing , vol.6 , pp. 101-111
    • Cowles, M.K.1
  • 18
    • 0030539336 scopus 로고    scopus 로고
    • Markov chain Monte Carlo convergence diagnostics: A comparative review
    • Cowles, M. K., & Carlin, B. (1996). Markov chain Monte Carlo convergence diagnostics: A comparative review. Journal of the American Statistical Association, 91, 883-904.
    • (1996) Journal of the American Statistical Association , vol.91 , pp. 883-904
    • Cowles, M.K.1    Carlin, B.2
  • 19
    • 27544504842 scopus 로고    scopus 로고
    • Making the most of what we have: A practical application of multidimensional item response theory in test scoring
    • de la Torre, J., & Patz, R. J. (2005). Making the most of what we have: A practical application of multidimensional item response theory in test scoring. Journal of Educational and Behavioral Statistics, 30, 295-311.
    • (2005) Journal of Educational and Behavioral Statistics , vol.30 , pp. 295-311
    • de la Torre, J.1    Patz, R.J.2
  • 20
    • 33646696643 scopus 로고    scopus 로고
    • Application of the bi-factor multidimensional item response theory model to testlet-based tests
    • DeMars, C. E. (2006). Application of the bi-factor multidimensional item response theory model to testlet-based tests. Journal of Educational Measurement, 43, 145-168.
    • (2006) Journal of Educational Measurement , vol.43 , pp. 145-168
    • Demars, C.E.1
  • 21
    • 34248166517 scopus 로고    scopus 로고
    • Guessing parameter estimates for multidimensional item response theory models
    • DeMars, C. E. (2007). "Guessing" parameter estimates for multidimensional item response theory models. Educational and Psychological Measurement, 67, 433-446.
    • (2007) Educational and Psychological Measurement , vol.67 , pp. 433-446
    • Demars, C.E.1
  • 22
    • 77956061963 scopus 로고    scopus 로고
    • Edwards, M. C. (2005a). A Markov chain Monte Carlo approach to confirmatory item factor analysis. Unpublished doctoral dissertation, University of North Carolina at Chapel Hill.
  • 23
    • 77956062657 scopus 로고    scopus 로고
    • Edwards, M. C. (2005b). MultiNorm: Multidimensional normal ogive item response theory analysis [Computer software].
  • 24
    • 33750161672 scopus 로고    scopus 로고
    • An empirical Bayes approach to subscore augmentation: How much strength can we borrow?
    • Edwards, M. C., & Vevea, J. L. (2006). An empirical Bayes approach to subscore augmentation: How much strength can we borrow? The Journal of Educational and Behavioral Statistics, 31, 241-259.
    • (2006) The Journal of Educational and Behavioral Statistics , vol.31 , pp. 241-259
    • Edwards, M.C.1    Vevea, J.L.2
  • 26
    • 0035534930 scopus 로고    scopus 로고
    • Bayesian estimation of a multilevel IRT model using Gibbs sampling
    • Fox, J.-P., & Glas, C. A. W. (2001). Bayesian estimation of a multilevel IRT model using Gibbs sampling. Psychometrika, 66, 269-286.
    • (2001) Psychometrika , vol.66 , pp. 269-286
    • Fox, J.-P.1    Glas, C.A.W.2
  • 28
    • 0001582213 scopus 로고    scopus 로고
    • Inference and monitoring convergence
    • W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (Eds.), London: Chapman and Hall
    • Gelman, A. (1996). Inference and monitoring convergence. In W. R. Gilks, S. Richardson, & D. J. Spiegelhalter (Eds.), Markov chain Monte Carlo in practice (pp. 131-143). London: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 131-143
    • Gelman, A.1
  • 30
    • 84972492387 scopus 로고
    • Inference from iterative simulation using multiple sequences (with discussion)
    • Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences (with discussion). Statistical Science, 7, 457-511.
    • (1992) Statistical Science , vol.7 , pp. 457-511
    • Gelman, A.1    Rubin, D.B.2
  • 32
    • 0001032163 scopus 로고
    • Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments
    • J. M. Bernardo, J. Berger, A. P. Dawid, and A. F. M. Smith (Eds.), Oxford: Oxford University Press
    • Geweke, J. (1992). Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In J. M. Bernardo, J. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 169-193). Oxford: Oxford University Press.
    • (1992) Bayesian Statistics 4 , pp. 169-193
    • Geweke, J.1
  • 34
    • 21144476248 scopus 로고
    • Full-information item bi-factor analysis
    • Gibbons, R. D., & Hedeker, D. R. (1992). Full-information item bi-factor analysis. Psychometrika, 57, 423-436.
    • (1992) Psychometrika , vol.57 , pp. 423-436
    • Gibbons, R.D.1    Hedeker, D.R.2
  • 35
    • 58149350433 scopus 로고    scopus 로고
    • On the psychometric validity of the domains of the pdsq: An illustration of the bi-factor item response theory model
    • Gibbons, R. D., Rush, A. J., & Immekus, J. C. (2009). On the psychometric validity of the domains of the pdsq: An illustration of the bi-factor item response theory model. Journal of Psychiatric Research, 43, 401-410.
    • (2009) Journal of Psychiatric Research , vol.43 , pp. 401-410
    • Gibbons, R.D.1    Rush, A.J.2    Immekus, J.C.3
  • 36
    • 0002517089 scopus 로고    scopus 로고
    • Introducing Markov chain Monte Carlo
    • W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (Eds.), New York: Chapman and Hall
    • Gilks, W. R., Richardson, S., & Spiegelhalter, D. J. (1996a). Introducing Markov chain Monte Carlo. In W. R. Gilks, S. Richardson, & D. J. Spiegelhalter (Eds.), Markov chain Monte Carlo in practice (pp. 1-19). New York: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 1-19
    • Gilks, W.R.1    Richardson, S.2    Spiegelhalter, D.J.3
  • 37
    • 0003860037 scopus 로고    scopus 로고
    • W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (Eds.), New York: Chapman and Hall
    • Gilks, W. R., Richardson, S., & Spiegelhalter, D. J. (Eds.) (1996b). Markov chain Monte Carlo in practice. New York: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice
  • 39
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov chains and their applications
    • Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97-109.
    • (1970) Biometrika , vol.57 , pp. 97-109
    • Hastings, W.K.1
  • 40
    • 0020850136 scopus 로고
    • Simulation run length control in the presence of an initial transient
    • Heidelberger, P., & Welch, P. D. (1983). Simulation run length control in the presence of an initial transient. Operations Research, 31, 1109-1144.
    • (1983) Operations Research , vol.31 , pp. 1109-1144
    • Heidelberger, P.1    Welch, P.D.2
  • 41
    • 34247364657 scopus 로고    scopus 로고
    • Practical issues in the application of item response theory: A demonstration using item form the Pediatric Quality of Life Inventory (PedsQL) 4.0 Generic Core Scales
    • Hill, C. D., Edwards, M. C., Thissen, D., Langer, M. M., Wirth, R. J., Burwinkle, T. M., et al. (2007). Practical issues in the application of item response theory: A demonstration using item form the Pediatric Quality of Life Inventory (PedsQL) 4. 0 Generic Core Scales. Medical Care, 45, S39-S47.
    • (2007) Medical Care , vol.45
    • Hill, C.D.1    Edwards, M.C.2    Thissen, D.3    Langer, M.M.4    Wirth, R.J.5    Burwinkle, T.M.6
  • 44
    • 17044390545 scopus 로고    scopus 로고
    • [Computer software], Chicago: Scientific Software International, Inc
    • Jöreskog, K. G., & Sörbom, D. (2003). LISREL 8. 54 [Computer software]. Chicago: Scientific Software International, Inc.
    • (2003) LISREL 8.54
    • Jöreskog, K.G.1    Sörbom, D.2
  • 45
    • 34250176929 scopus 로고    scopus 로고
    • Irt model selection methods for dichotomous items
    • Kang, T., & Cohen, A. S. (2007). Irt model selection methods for dichotomous items. Applied Psychological Measurement, 31, 331-358.
    • (2007) Applied Psychological Measurement , vol.31 , pp. 331-358
    • Kang, T.1    Cohen, A.S.2
  • 46
  • 50
    • 0033411905 scopus 로고    scopus 로고
    • A straightforward approach to Markov chain Monte Carlo methods for item response models
    • Patz, R. J., & Junker, B. W. (1999a). A straightforward approach to Markov chain Monte Carlo methods for item response models. Journal of Educational and Behavioral Statistics, 24, 146-178.
    • (1999) Journal of Educational and Behavioral Statistics , vol.24 , pp. 146-178
    • Patz, R.J.1    Junker, B.W.2
  • 51
    • 0033261632 scopus 로고    scopus 로고
    • Applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses
    • Patz, R. J., & Junker, B. W. (1999b). Applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses. Journal of Educational and Behavioral Statistics, 24, 342-366.
    • (1999) Journal of Educational and Behavioral Statistics , vol.24 , pp. 342-366
    • Patz, R.J.1    Junker, B.W.2
  • 53
    • 28444445926 scopus 로고    scopus 로고
    • R Development Core Team, Vienna: R Foundation for Statistical Computing. Retrieved from, Available from http://www. R-project. org
    • R Development Core Team (2005). R: A language and environment for statistical computing [Computer software]. Vienna: R Foundation for Statistical Computing. Retrieved from http://www. R-project. org. Available from http://www. R-project. org.
    • (2005) R: A language and environment for statistical computing [Computer software]
  • 54
    • 0000759236 scopus 로고
    • How many iterations in the Gibbs sampler?
    • J. M. Bernardo, J. Berger, A. P. Dawid, and A. F. M. Smith (Eds.), Oxford: Oxford University Press
    • Raftery, A. E., & Lewis, S. (1992). How many iterations in the Gibbs sampler? In J. M. Bernardo, J. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 763-773). Oxford: Oxford University Press.
    • (1992) Bayesian Statistics 4 , pp. 763-773
    • Raftery, A.E.1    Lewis, S.2
  • 55
    • 0001974429 scopus 로고    scopus 로고
    • Markov chain concepts related to sampling algorithms
    • W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (Eds.), New York: Chapman and Hall
    • Roberts, G. O. (1996). Markov chain concepts related to sampling algorithms. In W. R. Gilks, S. Richardson, & D. J. Spiegelhalter (Eds.), Markov chain Monte Carlo in practice (pp. 45-57). New York: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 45-57
    • Roberts, G.O.1
  • 56
    • 77956062989 scopus 로고    scopus 로고
    • Samejima, F. (1969). Psychometrika Monograph, No. 17: Estimation of latent ability using a response pattern of graded scores.
  • 57
    • 28844454343 scopus 로고    scopus 로고
    • High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature
    • Schilling, S., & Bock, R. D. (2005). High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature. Psychometrika, 70, 533-555.
    • (2005) Psychometrika , vol.70 , pp. 533-555
    • Schilling, S.1    Bock, R.D.2
  • 58
    • 77956057743 scopus 로고    scopus 로고
    • Segall, D. O. (2002). Confirmatory item factor analysis using Markov chain Monte Carlo estimation with applications to online calibration in CAT. Paper presented at the annual meeting of the National Council on Measurement in Education, New Orleans, LA.
  • 59
    • 0000592609 scopus 로고    scopus 로고
    • Bayesian sampling-based approach for factor analysis models with continuous and polytomous data
    • Shi, J.-Q., & Lee, S.-Y. (1998). Bayesian sampling-based approach for factor analysis models with continuous and polytomous data. British Journal of Mathematical and Statistical Psychology, 51, 233-252.
    • (1998) British Journal of Mathematical and Statistical Psychology , vol.51 , pp. 233-252
    • Shi, J.-Q.1    Lee, S.-Y.2
  • 60
    • 11844261472 scopus 로고    scopus 로고
    • Experiences with Markov chain Monte Carlo convergence assessment in two psychometric examples
    • Sinharay, S. (2004). Experiences with Markov chain Monte Carlo convergence assessment in two psychometric examples. Journal of Educational and Behavioral Statistics, 29, 461-488.
    • (2004) Journal of Educational and Behavioral Statistics , vol.29 , pp. 461-488
    • Sinharay, S.1
  • 61
    • 33744933187 scopus 로고    scopus 로고
    • Posterior predictive assessment of item response theory models
    • Sinharay, S. (2006). Posterior predictive assessment of item response theory models. Applied Psychological Measurement, 30, 298-321.
    • (2006) Applied Psychological Measurement , vol.30 , pp. 298-321
    • Sinharay, S.1
  • 62
    • 0000563849 scopus 로고
    • On the relationship between item response theory and factor analysis of discretized variables
    • Takane, Y., & de Leeuw, J. (1987). On the relationship between item response theory and factor analysis of discretized variables. Psychometrika, 52, 393-408.
    • (1987) Psychometrika , vol.52 , pp. 393-408
    • Takane, Y.1    de Leeuw, J.2
  • 64
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by data augmentation (with discussion)
    • Tanner, M. A., & Wong, W. H. (1987). The calculation of posterior distributions by data augmentation (with discussion). Journal of the American Statistical Association, 82, 528-550.
    • (1987) Journal of the American Statistical Association , vol.82 , pp. 528-550
    • Tanner, M.A.1    Wong, W.H.2
  • 67
    • 0002507596 scopus 로고    scopus 로고
    • Testlet response theory: An analog for the 3-PL useful in testlet-based adaptive testing
    • W. J. Lindenvan der and C. A. W. Glas (Eds.), Boston: Kluwer Academic
    • Wainer, H., Bradlow, E. T., & Du, Z. (2000). Testlet response theory: An analog for the 3-PL useful in testlet-based adaptive testing. In W. J. van der Linden & C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 245-270). Boston: Kluwer Academic.
    • (2000) Computerized Adaptive Testing: Theory and Practice , pp. 245-270
    • Wainer, H.1    Bradlow, E.T.2    Du, Z.3
  • 68
    • 84988141297 scopus 로고
    • Item clusters and computerized adaptive testing: A case for testlets
    • Wainer, H., & Kiely, G. (1987). Item clusters and computerized adaptive testing: A case for testlets. Journal of Educational Measurement, 24, 185-202.
    • (1987) Journal of Educational Measurement , vol.24 , pp. 185-202
    • Wainer, H.1    Kiely, G.2
  • 69
    • 0007366882 scopus 로고    scopus 로고
    • Augmented scores-"Borrowing strength" to compute scores based on a small number of items
    • D. Thissen and H. Wainer (Eds.), Mahwah: Lawrence Erlbaum Associates, Inc
    • Wainer, H., Vevea, J. L., Camacho, F., Reeve, B. B., Rosa, K., Nelson, L., et al. (2001). Augmented scores-"Borrowing strength" to compute scores based on a small number of items. In D. Thissen & H. Wainer (Eds.), Test scoring (pp. 347-387). Mahwah: Lawrence Erlbaum Associates, Inc.
    • (2001) Test Scoring , pp. 347-387
    • Wainer, H.1    Vevea, J.L.2    Camacho, F.3    Reeve, B.B.4    Rosa, K.5    Nelson, L.6
  • 70
    • 0036100904 scopus 로고    scopus 로고
    • A general Bayesian model for testlets: Theory and applications
    • Wang, X., Bradlow, E. T., & Wainer, H. (2002). A general Bayesian model for testlets: Theory and applications. Applied Psychological Measurement, 26, 109-128.
    • (2002) Applied Psychological Measurement , vol.26 , pp. 109-128
    • Wang, X.1    Bradlow, E.T.2    Wainer, H.3
  • 71
    • 34247192112 scopus 로고    scopus 로고
    • Item factor analysis: Current approaches and future directions
    • Wirth, R. J., & Edwards, M. C. (2007). Item factor analysis: Current approaches and future directions. Psychological Methods, 12, 58-79.
    • (2007) Psychological Methods , vol.12 , pp. 58-79
    • Wirth, R.J.1    Edwards, M.C.2


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