Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

Background Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues tha...

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Vydáno v:Health and quality of life outcomes Ročník 8; číslo 1; s. 81
Hlavní autoři: Scott, Neil W, Fayers, Peter M, Aaronson, Neil K, Bottomley, Andrew, de Graeff, Alexander, Groenvold, Mogens, Gundy, Chad, Koller, Michael, Petersen, Morten A, Sprangers, Mirjam AG
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 04.08.2010
BioMed Central Ltd
BMC
Témata:
Data Interpretation, Statistical
Female
Health aspects
Health Status Indicators
Humans
Logistic Models
Logistic regression
Male
Medicine
Medicine & Public Health
Psychometrics
Quality of Life
Quality of Life Research
Sample Size
Surveys and Questionnaires
Denmark
Netherlands
Germany
Differential Item Functioning Analysis
Differential Item Functioning
Item Response Theory
HRQoL Instrument
Ordinal Logistic Regression
ISSN:1477-7525, 1477-7525
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Popis
Shrnutí:Background Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application. Methods A review of logistic regression DIF analyses in HRQoL was undertaken. Methodological articles from other fields and using other DIF methods were also included if considered relevant. Results There are many competing approaches for the conduct of DIF analyses and many criteria for determining what constitutes significant DIF. DIF in short scales, as commonly found in HRQL instruments, may be more difficult to interpret. Qualitative methods may aid interpretation of such DIF analyses. Conclusions A number of methodological choices must be made when applying logistic regression for DIF analyses, and many of these affect the results. We provide recommendations based on reviewing the current evidence. Although the focus is on logistic regression, many of our results should be applicable to DIF analyses in general. There is a need for more empirical and theoretical work in this area.
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ISSN:1477-7525
1477-7525
DOI:10.1186/1477-7525-8-81