title: Chinese time trade-off values for EQ-5D health states.
abstract: OBJECTIVE
  To generate a Chinese general population-based three-level EuroQol five-dimensios (EQ-5D-3L) social value set using the time trade-off method.
  
  
  METHODS
  The study sample was drawn from five cities in China: Beijing, Guangzhou, Shenyang, Chengdu, and Nanjing, using a quota sampling method. Utility values for a subset of 97 health states defined by the EQ-5D-3L descriptive system were directly elicited from the study sample using a modified Measurement and Valuation of Health protocol, with each respondent valuing 13 of the health states. The utility values for all 243 EQ-5D-3L health states were estimated on the basis of econometric models at both individual and aggregate levels. Various linear regression models using different model specifications were examined to determine the best model using predefined model selection criteria.
  
  
  RESULTS
  The N3 model based on ordinary least square regression at the aggregate level yielded the best model fit, with a mean absolute error of 0.020, 7 and 0 states for which prediction errors were greater than 0.05 and 0.10, respectively, in absolute magnitude. This model passed tests for model misspecification (F = 2.7; P = 0.0509, Ramsey Regression Equation Specification Error Test), heteroskedasticity (χ(2) = 0.97; P = 0.3254, Breusch-Pagan/Cook-Weisberg test), and normality of the residuals (χ(2) = 1.285; P = 0.5259, Jarque-Bera test). The range of the predicted values (-0.149 to 0.887) was similar to those estimated in other countries.
  
  
  CONCLUSIONS
  The study successfully developed Chinese utility values for EQ-5D-3L health states using the time trade-off method. It is the first attempt ever to develop a standardized instrument for quantifying quality-adjusted life-years in China.
authors.affiliation: National School of Development, Peking University, Beijing, China.
authors.forename: Gordon G
authors.initials: GG
authors.lastname: Liu
authors.affiliation: School of Medicine and Health Management, Guiyang Medical University, Guiyang, China.
authors.forename: Hongyan
authors.initials: H
authors.lastname: Wu
authors.affiliation: South Carolina College of Pharmacy, University of South Carolina, Columbia, SC.
authors.forename: Minghui
authors.initials: M
authors.lastname: Li
authors.affiliation: Novo Nordisk (China) Pharmaceuticals Co., Ltd., Beijing, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Gao
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Electronic address: nan_luo@nuhs.edu.sg.
authors.forename: Nan
authors.initials: N
authors.lastname: Luo
mesh_terms: D000293:Adolescent; D000328:Adult; D002681:China; D003625:Data Collection; D005260:Female; D006304:Health Status; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D015233:Models, Statistical; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D011795:Surveys and Questionnaires; D013997:Time Factors; D055815:Young Adult
keywords: China; EQ-5D; TTO; social value set; utility