An alternative application of Rasch analysis to assess data from ophthalmic patient-reported outcome instruments

Richard N McNeely, Salissou Moutari, Samuel Arba-Mosquera, Shwetabh Verma and Jonathan E Moore

PLOS ONE, 2018, vol. 13, issue 6, 1-32

Abstract: Purpose: To highlight the potential shortcomings associated with the current use Rasch analysis for validation of ophthalmic questionnaires, and to present an alternative application of Rasch analysis to derive insights specific to the cohort of patients under investigation. Methods: An alternative application of Rasch analysis was used to investigate the quality of vision (QoV) for a cohort of 481 patients. Patients received multifocal intraocular lenses and completed a QoV questionnaire one and twelve months post-operatively. The rating scale variant of the polytomous Rasch model was utilized. The parameters of the model were estimated using the joint maximum likelihood estimation. Analysis was performed on data at both post-operative assessments, and the outcomes were compared. Results: The distribution of the location of symptoms altered between assessments with the most annoyed patients completely differing. One month post-operatively, the most prevalent symptom was starbursts compared to glare at twelve months. The visual discomfort from the most annoyed patients is substantially higher at twelve months. The current most advocated approach for validating questionnaires using Rasch analysis found that the questionnaire was “Rasch-valid” one month post-operatively and “Rasch-invalid” twelve months post-operatively. Conclusion: The proposed alternative application of Rasch analysis to questionnaires can be used as an effective decision support tool at population and individual level. At population level, this new approach enables one to investigate the prevalence of symptoms across different cohorts of patients. At individual level, the new approach enables one to identify patients with poor QoV over time. This study highlights some of the potential shortcomings associated with the current use of Rasch analysis to validate questionnaires.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0197503

DOI: 10.1371/journal.pone.0197503

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