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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 th...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924271/ https://www.ncbi.nlm.nih.gov/pubmed/20684767 http://dx.doi.org/10.1186/1477-7525-8-81 |
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author | 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 |
author_facet | 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 |
author_sort | Scott, Neil W |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2924271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29242712010-08-20 Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression 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 Health Qual Life Outcomes Research 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. BioMed Central 2010-08-04 /pmc/articles/PMC2924271/ /pubmed/20684767 http://dx.doi.org/10.1186/1477-7525-8-81 Text en Copyright ©2010 Scott et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research 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 Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title | Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title_full | Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title_fullStr | Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title_full_unstemmed | Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title_short | Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression |
title_sort | differential item functioning (dif) analyses of health-related quality of life instruments using logistic regression |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924271/ https://www.ncbi.nlm.nih.gov/pubmed/20684767 http://dx.doi.org/10.1186/1477-7525-8-81 |
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