Hi guys,
We've run a study using the Delphi method. Now, at the end, we'd like to conclude with a bigger implication. Does it make sense to you to have the results assessed by another, bigger group of respondents to confirm the study's results?
Thank you for your opinion.
Best wishes,
Martin
You can use a nonparametric statistics approach with the combination of the Delphi technique with the Kendall's test, where the coefficient of concordance (W) is obtained. For more details, please check the method used in the following article for the group of participants' data analysis.
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Hi Leandro Silvério ,
Thank you for your comment. Are you suggesting running the results through a bigger sample of respondents then?
Best,
Martin
Hello Martin,
The Delphi method is designed to structure a group consensus, and quantify the judgments of the experts (Waltz, Strickland, & Lenz, 2005). Regarding the number of samples, the panel may be as small as three members and as large as 80. In any case, please check the paper below as far as it may help you to have a more precise conclusion.
Article Stability of response characteristics of a Delphi panel: App...
Thanks :) However, I think we have an misunderstanding here. I’m well aware of the methodology. After being all the way through, I’m interested in more thoughts what to do next. After all, it’s just opinion of several people picked as a convenient sample, isn’t it? :)
Yes, that is correct. That way, in order to obtain a measure of consistency, Kendall coefficient of concordance can be used. The coefficient is a statistical test of agreement to test two or more sets of rankings in a contest (Israel, 2009). It varies between “0,” indicating no agreement between judges, and “+1,” indicating a complete agreement. That way you can turn from "just opinion of several people picked as a convenient sample" to "an agreement trend between the participants, where the not agreed responses will not be considered".
Oh wow, I wasn’t aware of that. I will check it get as much as I can from the answers. Thanks a lot!
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