We found a continuing trend towards conducting DCEs across a broader range of countries .
However , the trend towards including fewer attributes was reversed , whilst the trend towards interview-based DCEs reversed because of increased computer administration .
The trend towards using more flexible econometric models , including mixed logit and latent class , has also continued .
Reporting of monetary values has fallen compared with earlier periods , but the proportion of studies estimating trade-offs between health outcomes and experience factors , or valuing outcomes in terms of utility scores , has increased , although use of odds ratios and probabilities has declined .
The reassuring trend towards the use of more flexible and appropriate DCE design s and econometric methods has been reinforced by the increased use of qualitative methods to inform DCE processes and results .
However , qualitative research methods are being used less often to inform attribute selection , which may make DCEs more susceptible to omitted variable bias if the decision framework is not known prior to the research project .
Background Discrete choice experiments ( DCEs ) are increasingly used in health economics to address a wide range of health policy-related concerns .
Objective Broadly adopting the methodology of an earlier systematic review of health-related DCEs , which covered the period 2001–2008 , we report whether earlier trends continued during 2009–2012 .
Random Regret-Based Discrete-Choice Modelling: An Application to Healthcare
Background A new modelling approach for analysing data from discrete-choice experiments ( DCEs ) has been recently developed in transport economics based on the notion of regret minimization-driven choice behaviour . This so-called R and om Regret Minimization ( RRM ) approach forms an alternative to the dominant R and om Utility Maximization ( RUM ) approach . The RRM approach is able to model semi-compensatory choice behaviour and compromise effects , while being as parsimonious and formally tractable as the RUM approach . Objectives Our objectives were to introduce the RRM modelling approach to healthcare-related decisions , and to investigate its usefulness in this domain . Methods Using data from DCEs aim ed at determining valuations of attributes of osteoporosis drug treatments and human papillomavirus ( HPV ) vaccinations , we empirically compared RRM models , RUM models and Hybrid RUM – RRM models in terms of goodness of fit , parameter ratios and predicted choice probabilities . Results In terms of model fit , the RRM model did not outperform the RUM model significantly in the case of the osteoporosis DCE data ( p = 0.21 ) , whereas in the case of the HPV DCE data , the Hybrid RUM – RRM model outperformed the RUM model ( p < 0.05 ) . Differences in predicted choice probabilities between RUM models and ( Hybrid RUM- ) RRM models were small . Derived parameter ratios did not differ significantly between model types , but trade-offs between attributes implied by the two models can vary substantially . Conclusion Differences in model fit between RUM , RRM and Hybrid RUM – RRM were found to be small . Although our study did not show significant differences in parameter ratios , the RRM and Hybrid RUM – RRM models did feature considerable differences in terms of the trade-offs implied by these ratios . In combination , our results suggest that RRM and Hybrid RUM – RRM modelling approach hold the potential of offering new and policy-relevant insights for health research ers and policy makers
We found a continuing trend towards conducting DCEs across a broader range of countries .
However , the trend towards including fewer attributes was reversed , whilst the trend towards interview-based DCEs reversed because of increased computer administration .
The trend towards using more flexible econometric models , including mixed logit and latent class , has also continued .
Reporting of monetary values has fallen compared with earlier periods , but the proportion of studies estimating trade-offs between health outcomes and experience factors , or valuing outcomes in terms of utility scores , has increased , although use of odds ratios and probabilities has declined .
The reassuring trend towards the use of more flexible and appropriate DCE design s and econometric methods has been reinforced by the increased use of qualitative methods to inform DCE processes and results .
However , qualitative research methods are being used less often to inform attribute selection , which may make DCEs more susceptible to omitted variable bias if the decision framework is not known prior to the research project .
Background Discrete choice experiments ( DCEs ) are increasingly used in health economics to address a wide range of health policy-related concerns .
Objective Broadly adopting the methodology of an earlier systematic review of health-related DCEs , which covered the period 2001–2008 , we report whether earlier trends continued during 2009–2012 .