Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2016 | 2 (52) | 43-52

Article title

A polytomous item response theory models using R

Content

Title variants

PL
Politomiczne modele teorii odpowiedzi na pozycje testowe w programie R.

Languages of publication

EN

Abstracts

EN
Item response theory (IRT) is widely used in educational and psychological research to model how participants respond to test items in isolation and in bundles. Item response theory has replaced classical measurement theory as a framework for test development, scale constructions, scree reporting and test evaluation. The most popular of the item response models for multiple choice tests are the one-parameter (i. e. the Rasch model) and threeparameter models. This is the general framework for specifying the functional relationship between a respondent’s underlying latent trait level, commonly known as ability in educational testing, or the factor score in the factor analysis tradition and an item level stimulus. In this paper, arguments are offered for continuing research and applying multidimensional IRT models. The position is also taken that multi-parameter IRT models have potentially important roles to play in the advancement of measurement theory about which models to use should depend on model fit to the test data. All calculations are conducted in R available from CRAN which is a widely-used and well-known environment for statistical computing and graphics.

Contributors

References

  • Akaike H., 1974, A new look at the statistical model identification, IEEE Transactions on Automatic Control, 19 (6), pp. 716–723.
  • Andrich D., 2004, Controversy and the Rasch model: a characteristic of incompatible paradigms?, Medical Care, 42 (1 Supplement), pp. I–7.
  • Baker F.B., 1985, The basic of item response theory, College Park, MD: ERIC Clearinghouse on Assessment and Evaluation.
  • Bechtel, G.G., 1985, Generalizing the Rasch model for consumer rating scales, Marketing Science, 4 (1), pp. 62–73.
  • Birnbaum A., 1968, Some Latent Trait Models and Their Use in Inferring an Examinee`S Ability, [in:] Statistical Theories of Mental Test Scores, eds. F.M. Lord, M.R. Novick, Addison-Wesley, Reading, pp. 395–479.
  • Bock R.D., 1972, Estimating item parameters and latent ability when response are scored in two or more nominal categories, Psychometrika, 37, pp. 29–51.
  • Bock R., Lieberman M., 1970, Fitting a response model for n dichotomously scored items, Psychometrika, 35, pp. 179–197.
  • Christensen K.B., Kreiner S., Mesbah M., 2013, Rasch Models in Health, London–Hoboken: ISTE–Wiley.
  • De Ayala R.J., 2009, Theory and Practice of Item Response Theory, Guilford Publications.
  • Karlheinz R. and Melich A., 1992, Euro-Barometer 38.1: Consumer Protection and Perceptions of Science and Technology, INRA (Europe), Brussels [computer file].
  • Lord F.M., 1952, Theory of test scores, Psychometric Monographs, no. 7.
  • Lord F.M., 1980, Applications of Item Response Theory to Practical Testing Problems, Hillsdale: Lawrence Erlbaum.
  • Lord F.M., Novick M.R., 1968, Statistical theories of mental test scores (with contributions by A. Birnbaum), Reading, MA: Addison-Wesley.
  • Masters G.N., 1982, A Rasch model for partial credit scoring, Psychometrika, 47, pp. 149–174.
  • Masters G.N., Wright B. D. (1984), The essential process in a family of measurement models, Psychometrika, 49, pp. 529–544.
  • Ostini, R., Nering, M. L. (2005), Polytomous item response theory models. Thousand Oaks: Sage.
  • Rasch G., 1960, Probabilistic Models for some Intelligence and Attainment Tests, Danish Institute for Education Research, Copenhagen.
  • Rasch G., 1966, An Individualistic Approach to Item Analysis, [in:] P.F. Lazarsfeld, N.W. Henry (eds.), Readings in Mathematical Social Sciences, Cambridge: MIT Press, pp. 89–107.
  • Rasch G., 1977, On specific objectivity: An attempt at formalising the request for generality and validity of scientific statements, Danish Yearbook of Philosophy, 14, pp. 58-94.
  • Rizopoulos D., 2006, ltm: An R package for latent variable modelling and item response theory analyses, Journal of Statistical Software, 17(5), pp. 1–25, http://www.jstatsoft.org/v17/i05/.
  • Samejima F.,1969, Estimation of latent ability using a response pattern of graded scores, Psychometric Monograph, no. 17.
  • Samejima F., 1972, A general model for free-response data, Psychometrika Monograph, no. 18.
  • Schwarz G., 1978, Estimating the dimension of a model, Annals of Statistics, 6, pp. 461–464.
  • Thurstone L.L., 1928, Attitudes can be measured, American Journal of Sociology, 33, pp. 529–54.
  • Wright B.D., 1992, IRT in the 1990s: which models work best? 3PL or Rasch?, Rasch Measurement Transactions, 6 (1), pp. 196–200.
  • Wright B.D.,1997, A history of social science measurement, Educational Measurement: Issues and Practice, 16(4), pp. 33–45.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-301ae4de-dc7f-4c3d-a532-7e705c64b4c8
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.