Academic Journals Database
Disseminating quality controlled scientific knowledge

Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS): An item response theory approach

ADD TO MY LIST
 
Author(s): JEANNE A. TERESI | KATJA OCEPEK-WELIKSON | MARJORIE KLEINMAN | JOSEPH P. EIMICKE | PAUL K. CRANE | RICHARD N. JONES | JIN-SHEI LAI | SEUNG W. CHOI | RON D. HAYS | BRYCE B. REEVE | STEVEN P. REISE | PAUL A.PILKONIS | DAVID CELLA

Journal: Psychology Science Quarterly
ISSN 1866-6140

Volume: 51;
Issue: 2;
Start page: 148;
Date: 2009;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

ABSTRACT
The aims of this paper are to present findings related to differential item functioning (DIF) in the Patient Reported Outcome Measurement Information System (PROMIS) depression item bank, and to discuss potential threats to the validity of results from studies of DIF. The 32 depression items studied were modified from several widely used instruments. DIF analyses of gender, age and education were performed using a sample of 735 individuals recruited by a survey polling firm. DIF hypotheses were generated by asking content experts to indicate whether or not they expected DIF to be present, and the direction of the DIF with respect to the studied comparison groups. Primary analyses were conducted using the graded item response model (for polytomous, ordered response category data) with likelihood ratio tests of DIF, accompanied by magnitude measures. Sensitivity analyses were performed using other item response models and approaches to DIF detection. Despite some caveats, the items that are recommended for exclusion or for separate calibration were "I felt like crying" and "I had trouble enjoying things that I used to enjoy." The item, "I felt I had no energy," was also flagged as evidencing DIF, and recommended for additional review. On the one hand, false DIF detection (Type 1 error) was controlled to the extent possible by ensuring model fit and purification. On the other hand, power for DIF detection might have been compromised by several factors, including sparse data and small sample sizes. Nonetheless, practical and not just statistical significance should be considered. In this case the overall magnitude and impact of DIF was small for the groups studied, although impact was relatively large for some individuals.
Affiliate Program      Why do you need a reservation system?