Best–worst scaling is a judgment format in which participants are presented with K items and must choose the best and worst items from that set, along some underlying latent dimension. Best–worst scaling has seen recent use in natural-language processing and psychology to collect lexical semantic norms. In such applications, four items have always been presented on each trial. The present study provides reasoning that values other than 4 might provide better estimates of latent values. The results from simulation experiments and behavioral research confirmed this: Both suggest that, in the general case, six items per trial better reduces errors in the latent value estimates.
CITATION STYLE
Hollis, G. (2020). The role of number of items per trial in best–worst scaling experiments. Behavior Research Methods, 52(2), 694–722. https://doi.org/10.3758/s13428-019-01270-w
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