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    Is dimension order important when valuing health states using Discrete Choice Experiments including duration?

    246428_246428.pdf (595.1Kb)
    Access Status
    Open access
    Authors
    Mulhern, B.
    Norman, Richard
    Lorgelly, P.
    Lancsar, E.
    Ratcliffe, J.
    Brazier, J.
    Viney, R.
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Mulhern, B. and Norman, R. and Lorgelly, P. and Lancsar, E. and Ratcliffe, J. and Brazier, J. and Viney, R. 2017. Is dimension order important when valuing health states using Discrete Choice Experiments including duration? PharmacoEconomics. 35 (4): pp. 439-451.
    Source Title
    PharmacoEconomics
    DOI
    10.1007/s40273-016-0475-z
    ISSN
    1170-7690
    School
    Department of Health Policy and Management
    Remarks

    The final publication is available at Springer via http://doi.org/10.1007/s40273-016-0475-z

    URI
    http://hdl.handle.net/20.500.11937/35471
    Collection
    • Curtin Research Publications
    Abstract

    Background: Discrete choice experiments with duration (DCETTO) can be used to estimate utility values for preference-based measures, such as the EQ-5D-5L. For self-completion, the health dimensions are presented in a standard order. However, for valuation, this may result in order effects. Thus, it is important to understand whether health state dimension ordering affects values. The aim of this study was to examine the importance of dimension ordering on DCE values using EQ-5D-5L. Methods: A choice experiment presenting two health profiles and a third immediate death option was developed. A three-arm study was used, with the same 120 choice sets presented online across each arm (n = 360 per arm). Arm 1 presented the standard EQ-5D-5L dimension order, arm 2 randomised order between respondents, and arm 3 randomised within respondents. Conditional logit regression was used to assess model consistency, and scale parameter testing was used to assess model poolability. Results: There were minor inconsistencies across each arm, but the magnitudes of the coefficients produced were generally consistent. Arm 3 produced the largest range of utility values (1 to −0.980). Scale parameter testing suggested that the models did not differ, and the data could be pooled. Follow-up questions did not suggest variation in terms of difficulty. Conclusions: The results suggest that the level of randomisation used in DCE health state valuation studies does not significantly impact values, and dimension order may not be as important as other study design issues. The results support past valuation studies that use the standard order of dimensions.

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