Technical Papers

Title: Testing for the Optimal Number of Attributes in MaxDiff Questions

Description:

The authors investigate how the number of items per MaxDiff set affects dropout rates, survey length, positional bias, parameter equivalence, and predictive validity. Three commercial studies are analyzed, where the number of items per set varied from 3 items/set to 8 items/set. The number of items/set has the most influence on task length, with respondents taking significantly longer to complete 8 items/set rather than 3 items/set. Statistically significant differences among the parameters were found, but the authors note that the overall results would lead to similar managerial decisions. The predictive validity tests "hint that 3 items per question may produce slightly worse predictions than questions with more items." They conclude: "Given the slight evidence of poorer hit rates and poorer out-of-sample for 3 items per question we recommend using 4 or 5 items per question in maxdiff experiments."

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Applied methodologies

Technical papers

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