Encyclopedia of Clinical Neuropsychology

2018 Edition
| Editors: Jeffrey S. Kreutzer, John DeLuca, Bruce Caplan

Item Response Theory

  • Michael FranzenEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-57111-9_1209


Rasch modeling


Item response theory (IRT) was developed in response to observations that error terms in psychological measurement are frequently correlated with true scores. The measurement and analysis models of classical test theory assume that error terms are uncorrelated with true scores, that is, that the precision of measurement is equivalent across all levels of the construct being measured. The mathematical model is known as Rasch modeling, and typically the three-parameter Rasch model is invoked. The three parameters are the guessing parameter, the likelihood that an individual will get an item correct simply by guessing; the discrimination parameter or the probability of a correct response at a given level of difficulty; and the difficulty parameter or the level of skill in the construct where an item has 0.5 discrimination.

Current Knowledge

IRT allows an estimate of the precision of measurement for different levels of skill. IRT has facilitated the...

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

References and Readings

  1. Forero, C. G., & Maydeu-Olivares, A. (2009). Estimation of IRT graded response models: Limited versus full information methods. Psychological Methods, 14, 275–299.PubMedCrossRefGoogle Scholar
  2. Reise, S. P., Ainsworth, A. T., & Haviland, M. G. (2005). Item response theory: Fundamentals, applications, and promise in psychological research. Current Directions in Psychological Science, 14, 95–101.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Allegheny General HospitalPittsburghUSA