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Discrete choice experiments: a primer for the communication researcher.

Reed M Reynolds1, Lucy Popova2, Bo Yang3

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Discrete choice experiments (DCEs) are powerful tools for communication research, enabling the analysis of message attributes with fewer participants. This article provides resources to help communication scholars adopt DCEs for causal inference.

Keywords:
balanced incomplete block designsconjoint analysis (CA)discrete choice experimentsfractional factorial designsmessage evaluation tasks

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Area of Science:

  • Communication research
  • Behavioral science
  • Experimental methodology

Background:

  • Experiments are crucial for establishing causality in communication research.
  • Discrete Choice Experiments (DCEs) are underutilized in communication studies despite their prevalence in other fields.
  • DCEs offer a robust method for analyzing the impact of various message attributes.

Purpose of the Study:

  • To highlight the utility of Discrete Choice Experiments (DCEs) in communication research.
  • To demonstrate how DCEs can effectively disentangle the influence of multiple message attributes.
  • To provide resources for communication scholars to implement DCEs.

Main Methods:

  • DCEs utilize stimulus sets for direct comparisons.
  • Employ blocked and/or fractional factorial designs.
  • Leverage a wide range of analytical options for data interpretation.

Main Results:

  • DCEs allow for the disentanglement of numerous message attributes.
  • These experiments can achieve significant insights with modest sample sizes and reduced participant burden.
  • The methodology facilitates robust causal inference in communication studies.

Conclusions:

  • Discrete Choice Experiments (DCEs) offer a valuable and underused methodology for communication research.
  • Implementing DCEs can enhance the understanding of message attribute effects across diverse domains.
  • Resources are available to facilitate the adoption of DCEs by communication scholars and practitioners.