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The Product as a Fixed-Effect Fallacy

The arguments presented by Hassenzahl (this issue) and previous investigators in this area are based on the correlations, or lack of correlations, observed between different rating scales. This commentary is to make a methodological point about how experiments to examine correlations between product characteristics should ideally be carried out to make these arguments more convincing. The correlations reported are computed on averaged data and these averages may be computed in two ways: averaging over users or averaging over products. This short commentary draws attention to the fact that each of these two ways of summarizing the same set of data can result in rather different conclusions. The solution is to treat products in the same way as users. For an experiment to be considered valid, users need to be sampled at random from a well-defined population. I argue here that products (skins, ATMs, etc.) should similarly be sampled at random from a well-defined population of products, not selected according to some more or less well-defined criteria. Results can then be presented both averaging over users and averaging over products. Technically, products should be treated as a random variable, not a fixed effect. The title of the commentary is a reference to a famous article by Herbert Clark (1973), “The Language as a Fixed-Effect Fallacy,” that makes a conceptually similar point in the domain of psycholinguistics. HUMAN-COMPUTER INTERACTION, 2004, Volume 19, pp. 371–375 Copyright © 2004, Lawrence Erlbaum Associates, Inc.