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Selection of bolt-ons after factor analysis identification: are linear regression models a useful technique?

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posted on 25.02.2020 by Aureliano Paolo Finch, John Brazier, Clara Mukuria
It is now recognized that the EQ-5D may miss dimensions important for some conditions. When this happens, a possible solution is adding bolt-ons to expand its descriptive system. Previous bolt-on studies have identified potential candidates using information on validity in specific areas such as vision (1). Although this is a useful approach for identifying individual bolt-ons, it does not help in identifying what other dimensions may be missing from the EQ-5D. Factor analysis has been seen to be a potential approach for bolt-on identification. This techniques pinpoints to a list of factors, and items loading on them, that are not related to the EQ-5D latent constructs(2). These can be adapted / developed into bolt-ons. However, not all bolt-ons can be added to the EQ-5D simultaneously, as this would affect the measure’s acceptability and feasibility. Hence, methods to select bolt-ons from the identified list are needed. This study investigates the possibility of using linear regression models for the selection of bolt-ons after factor analytic identification

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