Estimating health state utility values from discrete choice experiments—A QALY space model approach

Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade-Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The condit...

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Main Authors: Gu, Y., Norman, Richard, Viney, R.
Format: Journal Article
Published: John Wiley & Sons Ltd. 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/15116
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author Gu, Y.
Norman, Richard
Viney, R.
author_facet Gu, Y.
Norman, Richard
Viney, R.
author_sort Gu, Y.
building Curtin Institutional Repository
collection Online Access
description Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade-Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The conditional logit is known for several limitations. In this paper, we propose two types of models based on the mixed logit: one using preference space and the other using quality-adjusted life year (QALY)space, a concept adapted from the willingness-to-pay literature. These methods are applied to a dataset collected using the EQ-5D. The results showcase the advantages of using QALY space and demonstrate that the preferred QALY space model provides lower estimates of the utility values than the conditional logit,with the divergence increasing with worsening health states.
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institution Curtin University Malaysia
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publishDate 2014
publisher John Wiley & Sons Ltd.
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spelling curtin-20.500.11937-151162017-09-13T15:04:06Z Estimating health state utility values from discrete choice experiments—A QALY space model approach Gu, Y. Norman, Richard Viney, R. Bayesian DCE EQ-5D QALY space Johnson’s SB mixed logit Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade-Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The conditional logit is known for several limitations. In this paper, we propose two types of models based on the mixed logit: one using preference space and the other using quality-adjusted life year (QALY)space, a concept adapted from the willingness-to-pay literature. These methods are applied to a dataset collected using the EQ-5D. The results showcase the advantages of using QALY space and demonstrate that the preferred QALY space model provides lower estimates of the utility values than the conditional logit,with the divergence increasing with worsening health states. 2014 Journal Article http://hdl.handle.net/20.500.11937/15116 10.1002/hec.3066 John Wiley & Sons Ltd. restricted
spellingShingle Bayesian
DCE
EQ-5D
QALY space
Johnson’s SB
mixed logit
Gu, Y.
Norman, Richard
Viney, R.
Estimating health state utility values from discrete choice experiments—A QALY space model approach
title Estimating health state utility values from discrete choice experiments—A QALY space model approach
title_full Estimating health state utility values from discrete choice experiments—A QALY space model approach
title_fullStr Estimating health state utility values from discrete choice experiments—A QALY space model approach
title_full_unstemmed Estimating health state utility values from discrete choice experiments—A QALY space model approach
title_short Estimating health state utility values from discrete choice experiments—A QALY space model approach
title_sort estimating health state utility values from discrete choice experiments—a qaly space model approach
topic Bayesian
DCE
EQ-5D
QALY space
Johnson’s SB
mixed logit
url http://hdl.handle.net/20.500.11937/15116