Robert W Massof1. 1. Lions Vision Research and Rehabilitation Center, Wilmer Ophthalmological Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. rmassof@lions.med.jhu.edu
Abstract
PURPOSE: The primary purpose of the study is to present and test a simple algorithm for scoring visual function questionnaires (VFQs) that approximates person measure estimates from Rasch analysis, does not introduce nonlinearities at extreme scores, and is insensitive to missing data. A secondary purpose is to test the hypothesis that all VFQs measure the same visual ability variable and can be calibrated to a common measurement scale. METHODS: Each of 407 consecutively recruited low vision patients were administered two of four visual function questionnaires: Activities of Daily Living Scale (ADVS), National Eye Institute Visual Functioning Questionnaire (NEI VFQ), 14-item Visual Functioning Index (VF-14), Visual Activities Questionnaire (VAQ). Separate Rasch analyses, using the Andrich rating scale model, were performed on responses to each of the four VFQs and again on the merged data of all instruments. An approximation of visual ability, based on average functional reserve and an inverse hyperbolic tangent transformation, is presented and tested by comparing visual ability estimates from the Rasch analyses to corresponding estimates from the approximations. RESULTS: Relative to person measure estimates from Rasch analysis, the approximations were observed to be linear and highly reliable (intraclass correlations ranged from 0.97 to 0.997). The measurement scale of each of the four instruments was observed to be a linear transformation of the measurement scale estimated from the merged responses of all four instruments. The approximation algorithm transforms rating scale responses for each instrument to a common measurement scale. By randomly censuring item responses for each subject, it was demonstrated that the approximation algorithm is robust and insensitive to missing data. CONCLUSIONS: A simple scoring algorithm based on an inverse hyperbolic tangent transformation of average functional reserve produces highly reliable approximations of visual ability estimated from Rasch analysis for the ADVS, NEI VFQ, VAQ, and VF-14. All four instruments measure the same visual ability variable in units that can be calibrated to a common measurement scale.
PURPOSE: The primary purpose of the study is to present and test a simple algorithm for scoring visual function questionnaires (VFQs) that approximates person measure estimates from Rasch analysis, does not introduce nonlinearities at extreme scores, and is insensitive to missing data. A secondary purpose is to test the hypothesis that all VFQs measure the same visual ability variable and can be calibrated to a common measurement scale. METHODS: Each of 407 consecutively recruited low visionpatients were administered two of four visual function questionnaires: Activities of Daily Living Scale (ADVS), National Eye Institute Visual Functioning Questionnaire (NEI VFQ), 14-item Visual Functioning Index (VF-14), Visual Activities Questionnaire (VAQ). Separate Rasch analyses, using the Andrich rating scale model, were performed on responses to each of the four VFQs and again on the merged data of all instruments. An approximation of visual ability, based on average functional reserve and an inverse hyperbolic tangent transformation, is presented and tested by comparing visual ability estimates from the Rasch analyses to corresponding estimates from the approximations. RESULTS: Relative to person measure estimates from Rasch analysis, the approximations were observed to be linear and highly reliable (intraclass correlations ranged from 0.97 to 0.997). The measurement scale of each of the four instruments was observed to be a linear transformation of the measurement scale estimated from the merged responses of all four instruments. The approximation algorithm transforms rating scale responses for each instrument to a common measurement scale. By randomly censuring item responses for each subject, it was demonstrated that the approximation algorithm is robust and insensitive to missing data. CONCLUSIONS: A simple scoring algorithm based on an inverse hyperbolic tangent transformation of average functional reserve produces highly reliable approximations of visual ability estimated from Rasch analysis for the ADVS, NEI VFQ, VAQ, and VF-14. All four instruments measure the same visual ability variable in units that can be calibrated to a common measurement scale.
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