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Improving the reliability of self-reported attribute non-attendance behaviour through the use of polytomous attendance scales

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  • Yuan, Yuan
  • You, Wen
  • Boyle, Kevin J.

Abstract

The literature in discrete choice modelling is increasingly recognizing the existence of attribute non-attendance, in which respondents ignore some attributes when answering an attribute-based question. This behaviour may present a serious problem for modelling and inference, because it violates fundamental assumptions of the random utility model on which choice models are based. In this study, we elicit attribute non-attendance using a six-point polytomous attendance scale, rather than restricting them to a dichotomous ignored/considered response, as in previous studies. Stated non-attendance has been found to be unreliable in previous studies, but polytomous attendance scales have the potential to address the sources of unreliability. Using data from a choice experiment in health economics, this study assesses the performance and consistency between empirical observations and theoretical expectations of a polytomous attendance scale. We find that the lowest point on the attendance scale is the part of the scale which corresponds best to attribute non-attendance, and that attendance scales longer than two or three points do not provide much additional information. Furthermore, the polytomous attendance scale had limited success in producing theoretically consistent results, suggesting that potential for polytomous attendance scales to produce more reliable attendance statements was not realized in this study.

Suggested Citation

  • Yuan, Yuan & You, Wen & Boyle, Kevin J., 2015. "Improving the reliability of self-reported attribute non-attendance behaviour through the use of polytomous attendance scales," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205688, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea15:205688
    DOI: 10.22004/ag.econ.205688
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    Keywords

    Health Economics and Policy; Research Methods/ Statistical Methods;

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