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Statistical analysis of EQ-5D profiles: does the use of value sets bias inference?

Parkin, D., Rice, N. & Devlin, N. (2008). Statistical analysis of EQ-5D profiles: does the use of value sets bias inference? (08/10). London, UK: Department of Economics, City University London.

Abstract

Health state profile data, such as those provided by the EQ-5D, are widely collected in clinical trials, population surveys and a growing range of other important health sector applications. However, these profile data are difficult to summarise to give an overall view of the health of a given population that can be analysed for differences between groups or within groups over time. A common way of short-cutting this problem is to transform profiles into a single number, or index, using sets of weights, often elicited from the general public in the form of values. Are there any problems with this procedure? In this paper we demonstrate the underlying effects of the use of value sets as a means of weighting profile data. We show that any set of weights introduces an exogenous source of variance to health profile data. These can distort findings about the significance of changes in health between groups or over time. No set of weights is neutral its effect. If a summary of patient reported outcomes is required, it may be better to use an instrument that yields this directly – such as the EQ VAS – along with the descriptive instrument. If this is not possible, researchers should have a clear rationale for their choice of weights; and be aware that those weighs may exert a non-trivial effect on their analysis. This paper focuses on the EQ-5D, but the arguments and their implications for statistical analysis are relevant to all health state descriptive systems.

Publication Type: Monograph (Discussion Paper)
Additional Information: © 2008 the authors
Publisher Keywords: Utility measurement, Health economics, Quality of Life, EQ-5D, Statistical inference
Subjects: H Social Sciences > HB Economic Theory
R Medicine > RA Public aspects of medicine
Departments: School of Policy & Global Affairs > Economics > Discussion Paper Series
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