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The authors compare a variety of different designs for choice experiments that satisfy the properties of the MNL model. These include both previously published and new design approaches: the latter are based on " shifting " design codes to create choice alternatives that maximize the number of attribute comparisons. An analysis of relative statistical(More)
In this paper we illustrate the benefits of forging a better alliance among behavioral, economic and statistical approaches to modeling consumer choice behavior. We focus on the problems that arise when building descriptive models of choice in evolving markets, where consumers are likely to have poorly-developed preferences and be influenced by beliefs(More)
BACKGROUND Additional insights into patient preferences can be gained by supplementing discrete choice experiments with best-worst choice tasks. However, there are no empirical studies illustrating the relative advantages of the various methods of analysis within a random utility framework. METHODS Multinomial and weighted least squares regression models(More)
* We would like to thank Grahame Dowling and participants at numerous conferences and seminars for comments on earlier versions of this paper. Amnesty International in the conduct of this work does not constitute either support for or views against the findings. ABSTRACT The present paper utilizes a random utility theoretic experimental design to provide(More)
Compared to many applied areas of economics, health economics has a strong tradition in eliciting and using stated preferences (SP) in policy analysis. Discrete choice experiments (DCEs) are one SP method increasingly used in this area. Literature on DCEs in health and more generally has grown rapidly since the mid-1990s. Applications of DCEs in health have(More)
We review current state-of-the-art practices for combining preference data from multiple sources and discuss future research possibilities. A central theme is that any one data source (e.g., a scanner panel source) is often insuf®cient to support tests of complex theories of choice and decision making. Hence, analysts may need to embrace a wider variety of(More)
It is often difficult to determine what actually was done in work involving data collected with stated preference surveys because the terms used to describe various procedures have ambiguous and sometimes conflicting meanings. Further, terms used to describe data collection procedures often are confounded with terms used to describe statistical techniques.(More)