Skip to main content
Log in

Item information and discrimination functions for trinary pcm items

  • Published:
Psychometrika Aims and scope Submit manuscript

Abstract

For trinary partial credit items the shape of the item information and the item discrimination function is examined in relation to the item parameters. In particular, it is shown that these functions are unimodal if δ2 − δ1 < 4 ln 2 and bimodal otherwi The locations and values of the maxima are derived. Furthermore, it is demonstrated that the value of the maximum is decreasing in δ2 − δ1. Consequently, the maximum of a unimodal item information function is always larger than the maximum of a bimodal one, and similarly for the item discrimination function.

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

  • Andrich, D. (1978). A rating formulation for ordered response categories.Psychometrika, 43, 561–573.

    Google Scholar 

  • Andrich, D. (1982). An extension of the Rasch model for ratings providing both location and dispersion parameters.Psychometrika, 47, 105–113.

    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 (Eds.),Statistical theories of mental test scores (pp. 395–479). Reading, MA: Addison-Wesley.

    Google Scholar 

  • Huynh, H. (1994). On equivalence between a partial credit item and a set of independent Rasch binary items.Psychometrika, 59, 111–119.

    Google Scholar 

  • Huynh, H. (1996). Decomposition of a Rasch partial credit item into independent binary and indecomposable trinary items.Psychometrika, 61, 31–39.

    Google Scholar 

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

    Google Scholar 

  • Masters, G. N. (1982). A Rasch model for partial credit scoring.Psychometrika, 47, 149–174.

    Google Scholar 

  • Mislevy, R., Johnson, E., & Muraki, E. (1992). Scaling procedures in NAEP.Journal of Educational Statistics, 17, 131–154.

    Google Scholar 

  • Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm.Applied Psychological Measurement, 16, 159–176.

    Google Scholar 

  • Muraki, E. (1993). Information functions of the generalized partial credit model.Applied Psychological Measurement, 17, 351–363.

    Google Scholar 

  • Rasch, G. (1960).Probabilistic models for some intelligence and attainment tests. Copenhagen: Danish Institute for Educational Research. (Reprinted in 1980 by The University of Chicago Press).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

The work reported herein was partially supported under the National Assessment of Educational Progress (Grant No. R999G30002; CFDA No. 84.999G) as administered by the Office of Educational Research and Improvement, US Department of Education.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Akkermans, W., Muraki, E. Item information and discrimination functions for trinary pcm items. Psychometrika 62, 569–578 (1997). https://doi.org/10.1007/BF02294643

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02294643

Key words

Navigation