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Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
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Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
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Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D

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Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D
Journal Article

Evaluating Equivalency between Response Systems: Application of the Rasch Model to a 3-Level and 5-Level EQ-5D

2007
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Overview
Background: Expansion of the EQ-5D health state classifier to 5 levels (EQ-5D-5L) has been proposed to improve discriminative and evaluative properties, but current preference-based algorithms were developed for a 3-level (EQ-5D-3L) structure. The objectives were to examine equivalency of meaning between 3L and 5L response systems, and to psychometrically derive a system of weights that facilitate conversion of 3L preference-based algorithms to a 5L system. Methods: Rasch models were used to examine the equivalency of the 3L and 5L systems using 2 datasets where health status was assessed using the 3L and 5L: a Dutch study of primarily hypothetical health state assessments and a US-based multicenter study of 423 cancer patients. Category-specific mean values of latent person parameters (using maximum likelihood estimation) for the levels of the 3L and 5L systems were estimated. Results: Means on the latent continuum pertaining to level 3 in the 5L system and level 2 in the 3L (some problems) were similar for both datasets, suggesting equivalence of these levels. Extremes of the 5L response structure consistently broadened the measurement continuum. By anchoring \"no problems\" as 0 disutility, disutility weights from EQ-5D-3L were transformed into weights for EQ-5D-5L using ratios of logit distances between person means for 5L and 3L calibrated for each dimension using the Rasch model. Conclusions: This study illustrates the rich potential for modern psychometric techniques both to examine equivalency when health status measures are modified as well as to inform preference-based measurement systems using existing value sets.