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Objectives. An alternative methodology is introduced to generate cardinal valuations of health states. This methodology is based on the ranking of differences between health states combined with an associated scaling model that transforms the individual rank data into group values on the interval level. Methods. Data were collected in a Dutch EuroQol EQ-5D valuation study, in which a representative sample (n = 212) of the Dutch population valued a set of 18 EQ-5D health states and death. Three computational steps were undertaken: 1) differences in visual analog scale (VAS) values were computed for each pair of health states based on individual data; 2) the rank ordering of these pairwise differences was derived; 3) nonmetric multidimensional scaling was used to recover cardinal scale values for each state based on these rankings of differences. Results. Scaling of ranked differences between health states using multidimensional scaling produced cardinal values that were nearly identical to the mean VAS valuations. The rank-based values explained 98% of the variance in the VAS values. Conclusion. Ordinal data collection techniques, combined with scaling models, may offer an attractive alternative to direct cardinal elicitation methods for valuing health states. [ABSTRACT FROM AUTHOR]

Objective. A basic mathematical routine called singular value decomposition (SVD) is introduced and applied to explore the applicability of this methodology in the context of health state valuations. Methods. SVD dissects a data matrix into 3 separatematrices that contain all the information present in the original data. Eachmatrix comprises a specific type of information. One matrix comprises arrays of weights that show the different valuation structures (i.e., similar ways among respondents to quantify specific sets of health states). A 2nd matrix with weights expresses how strongly each respondent's ratings are related to each of the valuation structures, and a 3rd matrix contains the percentages of variance associated with the valuation structures. SVD was applied to data from a group of 340 respondents who each gave a value to 16 health states using the time tradeoff (TTO) method and the visual analog scale (VAS). Results. SVD of the VAS data showed 1 distinct response pattern that accounted for 91.6% of the total variance. The contribution of the 1st component in the TTO data wasmuch lower (57.4%), and a 2nd component (15.6%) could be identified that reflected a distinct preference structure opposed to the 1st and principal component. Conclusions. Application of SVD to the TTO data revealed that respondents fell into 2 different groups in their TTO evaluations, but respondents weremore similar to each other in their VAS responses. The author discusses other applications of SVD to clinical research. [ABSTRACT FROM AUTHOR]