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A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function

BACKGROUND: The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0). The domi...

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Autores principales: Rand-Hendriksen, Kim, Augestad, Liv A, Dahl, Fredrik A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3284414/
https://www.ncbi.nlm.nih.gov/pubmed/22244261
http://dx.doi.org/10.1186/1478-7954-10-2
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author Rand-Hendriksen, Kim
Augestad, Liv A
Dahl, Fredrik A
author_facet Rand-Hendriksen, Kim
Augestad, Liv A
Dahl, Fredrik A
author_sort Rand-Hendriksen, Kim
collection PubMed
description BACKGROUND: The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0). The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. METHODS: We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. RESULTS: Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. DISCUSSION: Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm.
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spelling pubmed-32844142012-02-25 A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function Rand-Hendriksen, Kim Augestad, Liv A Dahl, Fredrik A Popul Health Metr Research BACKGROUND: The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0). The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. METHODS: We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. RESULTS: Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. DISCUSSION: Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm. BioMed Central 2012-01-13 /pmc/articles/PMC3284414/ /pubmed/22244261 http://dx.doi.org/10.1186/1478-7954-10-2 Text en Copyright ©2012 Rand-Hendriksen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Rand-Hendriksen, Kim
Augestad, Liv A
Dahl, Fredrik A
A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title_full A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title_fullStr A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title_full_unstemmed A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title_short A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function
title_sort critical re-evaluation of the regression model specification in the us d1 eq-5d value function
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3284414/
https://www.ncbi.nlm.nih.gov/pubmed/22244261
http://dx.doi.org/10.1186/1478-7954-10-2
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