Skip to main content
Log in

An investigation of hierarchical Bayes procedures in item response theory

  • Published:
Psychometrika Aims and scope Submit manuscript

Abstract

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item and ability parameters. Simulated data sets were analyzed via two joint and two marginal Bayesian estimation procedures. The marginal Bayesian estimation procedures yielded consistently smaller root mean square differences than the joint Bayesian estimation procedures for item and ability estimates. As the sample size and test length increased, the four Bayes procedures yielded essentially the same result.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Al-Karni, A. (1990).The impact of test structure on Bayesian test analysis. Unpublished doctoral dissertation, University of Wisconsin—Madison.

  • Baker, F. B. (1982).GENIRV: A program to generate item response vectors. Unpublished manuscript. Madison, WI: University of Wisconsin—Madison, Laboratory of Experimental Design.

    Google Scholar 

  • Baker, F. B., Al-Karni, A., & Al-Dosary, I. M. (1991). EQUATE: A computer program for the test characteristic curve method of IRT equating.Applied Psychological Measurement, 15, 78.

    Google Scholar 

  • Berger, J. O. (1985).Statistical decision theory and Bayesian analysis (2nd ed.). New York: Springer-Verlag.

    Google Scholar 

  • Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord & M. R. Novick,Statistical theories of mental test scores (pp. 395–479). Reading, MA: Addison-Wesley.

    Google Scholar 

  • Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm.Psychometrika, 46, 443–459.

    Article  Google Scholar 

  • Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood estimation from incomplete data via the EM algorithm (with discussion).Journal of the Royal Statistical Society, Series B, 39, 1–38.

    Google Scholar 

  • Gifford, J. A., & Swaminathan, H. (1990). Bias and the effect of priors in Bayesian estimation of parameters of item response models.Applied Psychological Measurement, 14, 33–43.

    Google Scholar 

  • Good, I. J. (1983). The robustness of a hierarchical model for multinomials and contingency tables. In G. E. P. Box, T. Leonard, & C.-F. Wu (Eds.),Scientific inference, data analysis, and robustness (pp. 191–211). New York: Academic Press.

    Google Scholar 

  • Harwell, M. R., & Baker, F. B. (1991). The use of prior distributions in marginalized Bayesian item parameter estimation: A didactic.Applied Psychological Measurement, 15, 375–389.

    Google Scholar 

  • Leonard, T. (1982). Comment on the paper by Lejeune and Faulkenberry.Journal of the American Statistical Association, 77, 657–658.

    Google Scholar 

  • Leonard, T., Hsu, J. S. J., & Tsui, K. W. (1989). Bayesian marginal inference.Journal of the American Statistical Association, 84, 1051–1058.

    Google Scholar 

  • Leonard, T., & Novick, M. R. (1985).Bayesian inference and diagnostics for the three parameter logistic model (ONR Technical Report 85-5). Iowa City, IA: The University of Iowa, CADA Research Group. (ERIC Document Reproduction Service No. ED 261 068)

    Google Scholar 

  • Lindley, D. V., & Smith, A. F. M. (1972). Bayes estimates for the linear model (with discussion).Journal of the Royal Statistical Society, Series B, 34, 1–41.

    Google Scholar 

  • Lord, F. M. (1980).Applications of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Mislevy, R. J. (1986). Bayes modal estimation in item response models.Psychometrika, 51, 177–195.

    Article  Google Scholar 

  • Mislevy, R. J., & Bock, R. D. (1989).PC-BILOG 3: Item analysis and test scoring with binary logistic models. Mooresville, IN: Scientific Software.

    Google Scholar 

  • O'Hagan, A. (1976). On posterior joint and marginal modes.Biometrika, 63, 329–333.

    Google Scholar 

  • Rigdon, S. E., & Tsutakawa, R. K. (1983). Parameter estimation in latent trait models.Psychometrika, 48, 567–574.

    Article  Google Scholar 

  • Seong, T.-J. (1990). Sensitivity of marginal maximum likelihood estimation of item and ability parameters to the characteristics of the prior ability distributions.Applied Psychological Measurement, 14, 299–311.

    Google Scholar 

  • Stocking, M. L., & Lord, F. M. (1983). Developing a common metric in item response theory.Applied Psychological Measurement, 7, 201–210.

    Google Scholar 

  • Swaminathan, H., & Gifford, J. A. (1982). Bayesian estimation in the Rasch model.Journal of Educational Statistics, 7, 175–191.

    Google Scholar 

  • Swaminathan, H., & Gifford, J. A. (1985). Bayesian estimation in the two-parameter logistic model.Psychometrika, 50, 349–364.

    Article  Google Scholar 

  • Swaminathan, H., & Gifford, J. A. (1986). Bayesian estimation in the three-parameter logistic model.Psychometrika, 51, 589–601.

    Article  Google Scholar 

  • Tierney, L., & Kadane, J. B. (1986). Accurate approximations for posterior moments and marginal densities.Journal of the American Statistical Association, 81, 82–86.

    Google Scholar 

  • Tsutakawa, R. K., & Johnson, J. C. (1990). The effect of uncertainty of item parameter estimation on ability estimates.Psychometrika, 55, 371–390.

    Article  Google Scholar 

  • Tsutakawa, R. K., & Lin, H. Y. (1986). Bayesian estimation of item response curves.Psychometrika, 51, 251–267.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

The authors wish to thank the Editor and anonymous reviewers for their insightful comments and suggestions.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, SH., Cohen, A.S., Baker, F.B. et al. An investigation of hierarchical Bayes procedures in item response theory. Psychometrika 59, 405–421 (1994). https://doi.org/10.1007/BF02296133

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02296133

Key words

Navigation