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Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework
by
Hardouin, Jean-Benoit
, Coste, Joël
, Sébille, Véronique
, Vanhaesebrouck, Alexis
, Rouquette, Alexandra
in
Analysis
/ Balances (scales)
/ Bias
/ Bioengineering
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer simulation
/ Data Interpretation, Statistical
/ Epidemiology
/ Health Status
/ Humans
/ Internet
/ Item response theory
/ Life Sciences
/ Literature reviews
/ Medical research
/ Medicine and Health Sciences
/ Models, Statistical
/ Outcome Assessment, Health Care - methods
/ Physical Sciences
/ Psychometrics - methods
/ Public health
/ Quality of Life
/ Rasch model
/ Research and Analysis Methods
/ Research design
/ Research methods
/ Social Sciences
/ Statistical analysis
/ Statistical methods
/ Statistical significance
/ Studies
/ Surveys and Questionnaires
2019
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Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework
by
Hardouin, Jean-Benoit
, Coste, Joël
, Sébille, Véronique
, Vanhaesebrouck, Alexis
, Rouquette, Alexandra
in
Analysis
/ Balances (scales)
/ Bias
/ Bioengineering
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer simulation
/ Data Interpretation, Statistical
/ Epidemiology
/ Health Status
/ Humans
/ Internet
/ Item response theory
/ Life Sciences
/ Literature reviews
/ Medical research
/ Medicine and Health Sciences
/ Models, Statistical
/ Outcome Assessment, Health Care - methods
/ Physical Sciences
/ Psychometrics - methods
/ Public health
/ Quality of Life
/ Rasch model
/ Research and Analysis Methods
/ Research design
/ Research methods
/ Social Sciences
/ Statistical analysis
/ Statistical methods
/ Statistical significance
/ Studies
/ Surveys and Questionnaires
2019
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Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework
by
Hardouin, Jean-Benoit
, Coste, Joël
, Sébille, Véronique
, Vanhaesebrouck, Alexis
, Rouquette, Alexandra
in
Analysis
/ Balances (scales)
/ Bias
/ Bioengineering
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer simulation
/ Data Interpretation, Statistical
/ Epidemiology
/ Health Status
/ Humans
/ Internet
/ Item response theory
/ Life Sciences
/ Literature reviews
/ Medical research
/ Medicine and Health Sciences
/ Models, Statistical
/ Outcome Assessment, Health Care - methods
/ Physical Sciences
/ Psychometrics - methods
/ Public health
/ Quality of Life
/ Rasch model
/ Research and Analysis Methods
/ Research design
/ Research methods
/ Social Sciences
/ Statistical analysis
/ Statistical methods
/ Statistical significance
/ Studies
/ Surveys and Questionnaires
2019
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Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework
Journal Article
Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework
2019
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Overview
The aims were to review practices concerning Differential Item Functioning (DIF) detection in composite measurement scales, particularly those used in health research, and to provide guidance on how to proceed if statistically significant DIF is detected.
This work specifically addressed the Rasch model which is the subject of growing interest in the field of health owing to its particularly advantageous properties. There were three steps: 1) Literature review to describe current practices; 2) Simulation study to determine under which conditions encountered in health research studies can erroneous conclusions be drawn from group comparisons when a scale is affected by DIF but which is not considered; 3) Based on steps 1 and 2, formulation of recommendations that were subsequently reviewed by leading internationally recognized experts.
Four key recommendations were formulated to help researchers to determine whether statistically significant DIF is meaningful in practice, according to the kind of DIF (uniform or non-uniform) and the DIF effect size.
This work provides the first recommendations on how to deal in practice with the presence of DIF in composite measurement scales used in health research studies.
Publisher
Public Library of Science,Public Library of Science (PLoS)
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