Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .
Estimating a preference-based index from the Japanese SF-36.
OBJECTIVE The main objective of the study was to estimate a preference-based Short Form (SF)-6D index from the SF-36 for Japan and compare it with the UK results . STUDY DESIGN AND SETTING The SF-6D was translated into Japanese . Two hundred and forty-nine health states defined by this version of the SF-6D were then valued by a representative sample of 600 members of the Japanese general population using st and ard gamble ( SG ) . These health-state values were modeled using classical parametric r and om-effect methods with individual-level data and ordinary least squares ( OLS ) on mean health-state values , together with a new nonparametric approach using Bayesian methods of estimation . RESULTS All parametric models estimated on Japanese data were found to perform less well than their UK counterparts in terms of poorer goodness of fit , more inconsistencies , larger prediction errors and bias , and evidence of systematic bias in the predictions . Nonparametric models produce a substantial improvement in out-of- sample predictions . The physical , role , and social dimensions have relatively larger decrements than pain and mental health compared with those in the United Kingdom . CONCLUSION The differences between Japanese and UK valuations of the SF-6D make it important to use the Japanese valuation data set estimated using the nonparametric Bayesian technique presented in this article
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .