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

Health and Quality of Life Outcomes

Research

Michael Koller¹  Mirjam AG Sprangers²  Morten A Petersen³  Mogens Groenvold⁴  Alexander de Graeff⁵  Neil K Aaronson⁶  Chad Gundy⁶  Andrew Bottomley⁷  Neil W Scott⁸  Peter M Fayers⁹ 

[1] Centre for Clinical Studies, University Hospital Regensburg, Regensburg, Germany;Department of Medical Psychology, Academic Medical Centre, University of Amsterdam, Netherlands;Department of Palliative Medicine, Bispebjerg Hospital, Copenhagen, Denmark;Department of Palliative Medicine, Bispebjerg Hospital, Copenhagen, Denmark;Institute of Public Health, University of Copenhagen, Denmark;Division of Medical Oncology, Department of Internal Medicine, University Medical Centre, Utrecht, Netherlands;Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, Netherlands;Quality of Life Department, European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium;Section of Population Health, University of Aberdeen, UK;Section of Population Health, University of Aberdeen, UK;Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway;

关键词: Differential Item Functioning;    Item Response Theory;    Ordinal Logistic Regression;    HRQoL Instrument;    Differential Item Functioning Analysis;   

DOI  :  10.1186/1477-7525-8-81

 received in 2009-12-17, accepted in 2010-08-04,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundDifferential 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.MethodsA 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.ResultsThere 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.ConclusionsA 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.

【 授权许可】

CC BY   
© Scott et al; licensee BioMed Central Ltd. 2010