Gao, Jie, & Alessandro Soranzo (2020, December). Applying Q-methodology to investigate people’s preferences for multivariate stimuli. Frontiers in Psychology: Quantitative Psychology and Measurement, 11, art 556509, 13 pp. (doi: 10.3389/fpsyg.2020.556509) (Link: (Open Access:

Abstract: This article serves as a step-by-step guide of a new application of Q-methodology to experiments investigating people’s preferences for multivariate stimuli. Q-methodology has been widely applied in fields such as sociology, education and political sciences but, despite its numerous advantages, it has not yet gained much attention from experimental psychologists. This may be due to the fact that psychologists examining preferences, often adopt stimuli resulting from a combination of characteristics from multiple variables, and in repeated measure designs. At present, Q methodology could not handle very well these stimuli. We therefore developed a novel analysis procedure allowing Q-methodology to handle these situations. This procedure can estimate the importance of a variable, which we refer to as its dominance. We also propose a protocol requiring five analysis of a decision process to estimate: 1) the preference of stimuli, 2) the dominance of variables, 3) the individual differences, 4) the interaction between individual differences and preference, and 5) the interaction between individual differences and dominance. The guide comes with a script developed in R (R Core Team, 2019) to run the five analysis; furthermore, we provide a case study with a detailed description of the procedure and corresponding results. This guide is particularly beneficial to conduct and analyse experiments in any research on people’s preferences, such as experimental aesthetics, prototype testing, visual perception (e.g., judgments of similarity/dissimilarity to a model), etc.

Jie Gao <> is in the Institute of Education, University College London, London; and Alessandro Soranzo <> is in the Department of Psychology, Sociology, and Politics, Sheffield Hallam University, Sheffield, UK.

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