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 .
Mapping the relationship between clinical and quality-of-life outcomes in patients with ankylosing spondylitis
ABSTRACT Aim : To map health-related quality of life ( Qol ) with clinical parameters BASFI and ASDAS-CRP measure , and other covariates . Methods : Our prospect i ve multicenter non-interventional observation study of ankylosing spondylitis ( AS ) collected data about QoL and clinical outcomes on the initial and four subsequent visits . We employed simple linear regression analysis of a  cross-sectional  data set , and fixed effect , r and om effect and pooled linear regression of a longitudinal data set . Results : We showed that BASFI and ASDAS-CRP are very strong , robust predictors of EQ-5D utilities in all regression specifications together with sex ( female ) , invalidity , and activity impairment . Additionally , the longitudinal regression analysis showed that a fixed effect model may be a viable alternative to the most commonly used r and om effect model or pooled linear regression due to the nature of our data set . Conclusion : This is one of the first studies using a fixed effect model in longitudinal patient-level data , although , this method has been widely used in economics
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 .