Empirical investigation of experimental design properties of discrete choice experiments in health care
Experimental design is critical to valid inference from the results of discrete choice experiments (DCEs). In healtheconomics, DCEs have placed limited emphasis on experimental design, typically employing relatively smallfractional factorial designs, which allow only strictly linear additive utility functions to be estimated. The extensiveliterature on optimal experimental design outside health economics has proposed potentially desirable designproperties, such as orthogonality, utility balance and level balance. However, there are trade-offs between theseproperties and emphasis on some properties may increase the random variability in responses, potentially biasingparameter estimates.This study investigates empirically the design properties of DCEs, in particular, the optimal method of combiningalternatives in the choice set. The study involves a forced choice between two alternatives (treatment and nontreatmentfor a hypothetical health care condition), each with three, four-level, alternative-specific attributes. Threeexperimental design approaches are investigated: a standard six-attribute, orthogonal main effects design; a designthat combines alternatives to achieve utility balance, ensuring no alternatives are dominated; and a design- thatcombines alternatives randomly. The different experimental designs did not impact on the underlying parameterestimates, but imposing utility balance increases the random variability of responses.
Year of publication: |
2004
|
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Authors: | Savage Elizabeth ; Viney Rosalie ; Louviere Jordan |
Publisher: |
Lawrence Erlbaum Association |
Saved in:
freely available
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