Quality of Life Research

, Volume 16, Issue 6, pp 981–990 | Cite as

Differential item functioning impact in a modified version of the Roland–Morris Disability Questionnaire

  • Paul K. CraneEmail author
  • Karynsa Cetin
  • Karon F. Cook
  • Kurt Johnson
  • Richard Deyo
  • Dagmar Amtmann
Original Paper



To evaluate a modified version of the Roland–Morris Disability Questionnaire for differential item functioning (DIF) related to several covariates.


DIF occurs in an item when, after controlling for the underlying trait measured by the test, the probability of endorsing the item varies across groups.


Secondary data analysis of two studies of participants with back pain (total n = 875). We used a hybrid item response theory/ logistic regression approach for detecting DIF. We obtained scores that accounted for DIF. We evaluated the impact of DIF on individual and group scores, and compared scores that ignored or accounted for DIF in terms of the strength of association with SF-36 subscale scores.


DIF was found in 18/23 items. Salient scale-level differential functioning was found related to age, education, and employment. Overall 24 participants (3%) had salient scale-level differential functioning. Mean scores across demographic groups differed minimally when accounting for DIF. The strength of association of scores with SF-36 scores was similar for scores that ignored and scores that accounted for DIF.


The modified version of the Roland–Morris Disability Questionnaire appears to have largely negligible DIF related to the covariates assessed here.


Differential item functioning Item response theory Logistic regression Test bias 



2-parameter logistic model. In this parametric item response theory model, two parameters are modeled for each item: item difficulty and item discrimination


Differential item functioning. DIF occurs when an item has different statistical properties in different groups when controlling for the underlying trait or ability measured by the test


Item response theory. This is a technique for analyzing item-level test data based on the premise that item responses are a function of the relationship between an underlying latent trait and characteristics of the item


Sickness Impact Profile. This is a patient-reported outcome measure of the impact of illnesses


Seattle Lumbar Imaging Project, one of the two datasets of low back pain subjects analyzed in this study



Data were collected under the auspices of grants P60 AR48093 from the National Institutes of Health, National Institute for Arthritis, Musculoskeletal, and Skin Diseases, and HS-09499 from the Agency for Healthcare Research and Quality. Data were analyzed under the auspices of U01AR52171-01 from the National Institutes of Health, National Institute of Arthritis and Musculoskeletal and Skin Diseases. Data collection and analyses were reviewed by the University of Washington’s Institutional Review Board.


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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Paul K. Crane
    • 1
    Email author
  • Karynsa Cetin
    • 2
  • Karon F. Cook
    • 2
  • Kurt Johnson
    • 2
  • Richard Deyo
    • 1
  • Dagmar Amtmann
    • 2
  1. 1.Department of MedicineUniversity of Washington, Harborview Medical CenterSeattleUSA
  2. 2.Department of Rehabilitation MedicineUniversity of WashingtonSeattleUSA

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