Dear Editors-in-Chief,
We were interested to read the paper by Busija L and colleagues that was published in Osteoarthritis and Cartilage in Aug 2016
1
. The authors aimed to develop the OsteoArthritis Questionnaire (OA-Quest) for measuring the potentially modifiable burden of osteoarthritis. Performance of OA-Quest was assessed using exploratory factor analysis (EFA), Rasch modeling, and confirmatory factor analysis (CFA). The results have demonstrated the OA-Quest can be suitable for capturing the broad range of outcomes relevant to people with osteoarthritis1
.Although the statistical method was correct and the data were interesting, some methodological and statistical issues should be considered. The authors point out in their conclusion that OA-Quest is a valid and reliable tool for measuring broad range of osteoarthritis burden, we think such conclusion is an optimistic interpretation. Conducting EFA and CFA on same dataset is one of common mistakes. As a general rule, we need at least two independent dataset that explored solutions from EFA in dataset 1 would be externally validated using CFA in dataset 2
2
. Investigators used CFA to assess the robustness of results from an EFA in independent data sets or testing a proposed structure based on previously studies in a new data set and not the original data set3
, 4
, 5
.Author contributions
All authors were involved in the manuscript conception, design, drafting and revising, and final approval of the submitted version.
Conflict of interest
The authors have nothing to disclose.
Acknowledgment
The authors would like to thanks statistics consultants of Research Development Center of Sina Hospital for their technical assistance. This work was not supported by any organization.
References
- Development and preliminary evaluation of the OsteoArthritis Questionnaire (OA-Quest): a psychometric study.Osteoarthritis Cartilage. 2016; 24: 1357-1366
- Statistical Methods for Health Care Research. vol. 1. Lippincott Williams & Wilkins, 2005
- Translation, adaptation, and validation of hindi version of the pain catastrophizing scale: statistical issues of confirmatory factor analysis to avoid misinterpretation.Pain Med. 2016; ([Epub ahead of print])
- The cyberchondria severity scale (CSS): German validation and development of a short form.Int J Behav Med. 2016; 23: 595-605
- Development of a measure to evaluate gains among Spanish dementia caregivers: the gains associated with caregiving (GAC) scale.Arch Gerontol Geriatr. 2016; 68: 76-83
Article info
Publication history
Published online: November 02, 2016
Accepted:
October 5,
2016
Received:
September 28,
2016
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© 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd.
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