Evidence map›Paper›PMID 28927468›Full record

ArticleHealth and quality of life outcomes2017

Recent advances in analysis of differential item functioning in health research using the Rasch model.

Curt Hagquist, David Andrich

Abstract read
In one paragraph

Article in Health and quality of life outcomes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed.

  1. Trial
  2. Rasch Analysis and Interval-Level Scaling of the Positive and Negative Affect Schedule (PANAS) Across Cultures.International journal of psychology : Journal international de psychologie · 2026
    Article
  3. Article
  4. Article
  5. Psychometric evaluation of the Chinese CancerSupportSourceHealth and quality of life outcomes · 2026
    Article
  6. The Patient Reported Inventory of Self-Management of Chronic Conditions (PRISM-CC): testing for bias across patient characteristics and languages.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Curt HagquistCentre for Research on Child and Adolescent Mental Health, Karlstad University, SE-651 88, Karlstad, Sweden. curt.hagquist@kau.se.
David AndrichGraduate School of Education, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRasch analysis with a focus on Differential Item Functioning (DIF) is increasingly used for examination of psychometric properties of health outcome measures. To take account of DIF in order to retain precision of measurement, split of DIF-items into separate sample specific items has become a frequently used technique. The purpose of the paper is to present and summarise recent advances of analysis of DIF in a unified methodology. In particular, the paper focuses on the use of analysis of variance (ANOVA) as a method to simultaneously detect uniform and non-uniform DIF, the need to distinguish between real and artificial DIF and the trade-off between reliability and validity. An illustrative example from health research is used to demonstrate how DIF, in this case between genders, can be identified, quantified and under specific circumstances accounted for using the Rasch model.

methodsRasch analyses of DIF were conducted of a composite measure of psychosomatic problems using Swedish data from the Health Behaviour in School-aged Children study for grade 9 students collected during the 1985-2014 time periods.

resultsThe procedures demonstrate how DIF can be identified efficiently by ANOVA of residuals, and how the magnitude of DIF can be quantified and potentially accounted for by resolving items according to identifiable groups and using principles of test equating on the resolved items. The results of the analysis also show that the real DIF in some items does affect person measurement estimates.

conclusionsFirstly, in order to distinguish between real and artificial DIF, the items showing DIF initially should not be resolved simultaneously but sequentially. Secondly, while resolving instead of deleting a DIF item may retain reliability, both options may affect the content validity negatively. Resolving items with DIF is not justified if the source of the DIF is relevant for the content of the variable; then resolving DIF may deteriorate the validity of the instrument. Generally, decisions on resolving items to deal with DIF should also rely on external information.

Indexed as

Quality of LifeAnalysis of VarianceChildFemaleHumansMaleOutcome Assessment, Health CarePsychometricsPsychophysiologic DisordersReproducibility of ResultsSurveys and QuestionnairesSwedenAnalysis of varianceDifferential Item Functioning (DIF)HealthRaschReal and artificial DIFValidity and reliability

Identifiers

PMID28927468
PMCPMC5606090

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.