Benjamin M. Craig|Jan J. V. Busschbach|Joshua A. Salomon
Modeling Ranking, Time Trade-Off, and Visual Analog Scale Values for EQ-5D Health States
Moffitt Cancer Center|University of South Florida|Harvard Global Health Institute|Harvard University|Erasmus University Rotterdam|Erasmus MC|Moffitt Cancer Center|University of South Florida|Erasmus University Rotterdam|Erasmus MC|Harvard Global Health Institute|Harvard University|Moffitt Cancer Center|University of South Florida|Erasmus University Rotterdam|Erasmus MC|Harvard Global Health Institute|Harvard University
rising interest eliciting health state valuations using rankings due relative simplicity ordinal measurement methods may offer attractive practical alternative cardinal methods time tradeoff tto visual analog scale vas article explore alternative models estimating cardinal health state values rank responses unique multicountry database highlight estimation challenge pertaining health states perfect health nonoptimal gap propose analytic solution ameliorate problemusing standardized protocol developed euroqol group rank vas tto responses collected 43 health states 8 countries slovenia argentina denmark japan netherlands spain united kingdom united states yielding sample 179431 state responses 11483 subjects states described using eq5d system allows 3 different possible levels 5 different dimensions health estimated conditional logit probit regression models rank responses regressions included 17 health state attribute variables reflecting specific levels dimension counts different levels across dimensions flexible specification accommodates previously published valuation models models applied united kingdom united states addition fitting standard conditional logit probit models assume equal variance across health states homoscedasticity examined heteroscedastic probit model assumes variance 2 points anchoring scale optimal health dead relaxes equalvariance assumption states rankbased predictions 243 unique states defined eq5d system compared predictions conventional linear models fitted tto vas responsesby construction tto vas models assume variance around anchoring states optimal health dead mimicking assumption probit rank models helps dissolve nonoptimal gap states variances tto vas negatively associated mean values contradict assumption homoscedasticity estimated health state values heteroscedastic probit model ranking data highly correlated predictions tto vas models 243 eq5d states vas rankbased estimates lins rho measure agreement 098 mean absolute difference 0028 corresponding measures agreement rank tto estimates 096 012 similar agreement vas ttorankbased valuation techniques offer advantages flexibility generalizability ease administration may attractive substitutes tto vas measurement societal values health outcomes