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Related Experiment Videos

Effects coding in discrete choice experiments.

Mickael Bech1, Dorte Gyrd-Hansen

  • 1University of Southern Denmark, Institute of Public Health, Odense C, Denmark. mbe@sam.sdu.dk

Health Economics
|April 27, 2005
PubMed
Summary
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Dummy coding in discrete choice experiments can lead to misinterpretations when a fixed comparator is included. Effects coding offers a solution to avoid these analytical pitfalls and ensure accurate results.

Area of Science:

  • Econometrics
  • Behavioral Economics
  • Experimental Design

Background:

  • Discrete choice experiments (DCEs) are widely used in various fields.
  • Dummy coding is a common method for including reference alternatives.
  • Potential issues arise when using dummy coding with a fixed comparator in DCEs.

Purpose of the Study:

  • To highlight the inherent problems of dummy coding in DCEs with a fixed comparator.
  • To illustrate potential misinterpretations stemming from unawareness of these problems.
  • To present effects coding as a superior alternative.

Main Methods:

  • Analysis of discrete choice experiment design.
  • Comparison of dummy coding and effects coding methodologies.
  • Illustrative examples of coding-induced misinterpretations.

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Main Results:

  • Dummy coding with a fixed comparator can obscure or misrepresent parameter estimates.
  • Misinterpretations arise from the baseline comparison implicitly defined by dummy coding.
  • Effects coding provides a more intuitive and accurate representation of attribute effects.

Conclusions:

  • Researchers must be cautious when applying dummy coding in DCEs with fixed comparators.
  • Effects coding is recommended to prevent misinterpretations and ensure valid analysis.
  • Understanding coding methods is crucial for accurate DCE results.