Literature DB >> 27987630

Order of Presentation of Dimensions Does Not Systematically Bias Utility Weights from a Discrete Choice Experiment.

Richard Norman1, Georg Kemmler2, Rosalie Viney3, A Simon Pickard4, Eva Gamper2, Bernhard Holzner2, Virginie Nerich5, Madeleine King6.   

Abstract

BACKGROUND: Discrete choice experiments (DCEs) are increasingly used to value aspects of health. An issue with their adoption is that results may be sensitive to the order in which dimensions of health are presented in the valuation task. Findings in the literature regarding order effects are discordant at present.
OBJECTIVES: To quantify the magnitude of order effect of quality-of-life (QOL) dimensions within the context of a DCE designed to produce country-specific value sets for the EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D), a new utility instrument derived from the widely used cancer-specific QOL questionnaire, the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30.
METHODS: The DCE comprised 960 choice sets, divided into 60 versions of 16 choice sets, with each respondent assigned to a version. Within each version, the order of QLU-C10D QOL dimensions was randomized, followed by life duration in the last position. The DCE was completed online by 2053 individuals in France and Germany. We analyzed the data with a series of conditional logit models, adjusted for repeated choices within respondent. We used F tests to assess order effects, correcting for multiple hypothesis testing.
RESULTS: Each F test failed to reject the null hypothesis of no position effect: 1) all QOL order positions considered jointly; 2) last QOL position only; 3) first QOL position only. Furthermore, the order coefficients were small relative to those of the QLU-C10D QOL dimension levels.
CONCLUSIONS: The order of presentation of QOL dimensions within a DCE designed to provide utility weights for the QLU-C10D had little effect on level coefficients of those QOL dimensions.
Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  dimension order effects; discrete choice experiment, QLU-C10D, utility

Mesh:

Year:  2016        PMID: 27987630     DOI: 10.1016/j.jval.2016.07.003

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  6 in total

1.  Is Dimension Order Important when Valuing Health States Using Discrete Choice Experiments Including Duration?

Authors:  Brendan Mulhern; Richard Norman; Paula Lorgelly; Emily Lancsar; Julie Ratcliffe; John Brazier; Rosalie Viney
Journal:  Pharmacoeconomics       Date:  2017-04       Impact factor: 4.981

2.  The FACT-8D, a new cancer-specific utility algorithm based on the Functional Assessment of Cancer Therapies-General (FACT-G): a Canadian valuation study.

Authors:  Helen McTaggart-Cowan; Madeleine T King; Richard Norman; Daniel S J Costa; A Simon Pickard; Rosalie Viney; Stuart J Peacock
Journal:  Health Qual Life Outcomes       Date:  2022-06-16       Impact factor: 3.077

3.  Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.

Authors:  Mina Bahrampour; Joshua Byrnes; Richard Norman; Paul A Scuffham; Martin Downes
Journal:  Eur J Health Econ       Date:  2020-05-04

4.  Australian Utility Weights for the EORTC QLU-C10D, a Multi-Attribute Utility Instrument Derived from the Cancer-Specific Quality of Life Questionnaire, EORTC QLQ-C30.

Authors:  Madeleine T King; Rosalie Viney; A Simon Pickard; Donna Rowen; Neil K Aaronson; John E Brazier; David Cella; Daniel S J Costa; Peter M Fayers; Georg Kemmler; Helen McTaggart-Cowen; Rebecca Mercieca-Bebber; Stuart Peacock; Deborah J Street; Tracey A Young; Richard Norman
Journal:  Pharmacoeconomics       Date:  2018-02       Impact factor: 4.981

5.  Discrete Choice Experiments in Health Economics: Past, Present and Future.

Authors:  Vikas Soekhai; Esther W de Bekker-Grob; Alan R Ellis; Caroline M Vass
Journal:  Pharmacoeconomics       Date:  2019-02       Impact factor: 4.981

6.  EORTC QLU-C10D value sets for Austria, Italy, and Poland.

Authors:  E M Gamper; M T King; R Norman; F Efficace; F Cottone; B Holzner; G Kemmler
Journal:  Qual Life Res       Date:  2020-05-26       Impact factor: 4.147

  6 in total

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