The EQ-5D index is widely used to assess the preference-based health status. In this paper, we examine the analytical issues of regression models for the US preference-based EQ-5D index score. We propose a two-part approach to model the special features of the EQ-5D index. The first part is a logistic model for the probability of reaching the maximum score 1.0. The second part is a model for the rest of the scores that are less than 1.0, which can be a least squares regression with robust standard errors for the conditional mean, or a quantile regression for conditional quantiles such as the median. We show that the two-part model has some desirable features that are not available in the previously published regression methods for the EQ-5D index. We illustrate the proposed approach with data from the Medical Expenditure Panel Survey. The proposed method may be used for other utility or health related quality of life scores of similar features.
- Health related quality of life
- Quantile regression
- Sandwich variance estimator
- Two-part model
ASJC Scopus subject areas
- Health Policy
- Public Health, Environmental and Occupational Health