Item-score reliability in empirical-data sets and its relationship with other item indices

E.A.O. Zijlmans, J. Tijmstra, L.A. van der Ark, K. Sijtsma

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
52 Downloads (Pure)

Abstract

Reliability is usually estimated for a total score, but it can also be estimated for item scores. Item-score reliability can be useful to assess the repeatability of an individual item score in a group. Three methods to estimate item-score reliability are discussed, known as method MS, method λ6, and method CA. The item-score reliability methods are compared with four well-known and widely accepted item indices, which are the item-rest correlation, the item-factor loading, the item scalability, and the item discrimination. Realistic values for item-score reliability in empirical-data sets are monitored to obtain an impression of the values to be expected in other empirical-data sets. The relation between the three item-score reliability methods and the four well-known item indices are investigated. Tentatively, a minimum value for the item-score reliability methods to be used in item analysis is recommended.
Keywords Coefficient λ6, correction for attenuation, item discrimination, item-factor loading, item-rest correlation, item scalability, item-score reliability
Original languageEnglish
Article number998-1020
JournalEducational and Psychological Measurement
Volume78
Issue number6
DOIs
Publication statusPublished - 2018

Keywords

  • ASSOCIATION
  • Coefficient lambda(6)
  • IRT
  • JOB-SATISFACTION
  • MODEL
  • MOKKEN SCALE ANALYSIS
  • PERSONALITY
  • SINGLE-ITEM
  • VALIDITY
  • correction for attenuation
  • item discrimination
  • item scalability
  • item-factor loading
  • item-rest correlation
  • item-score reliability

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