Precise models deserve precise measures: A methodological dissection
AbstractThe recognition heuristic (RH) --- which predicts non-compensatory reliance on recognition in comparative judgments --- has attracted much research and some disagreement, at times. Most studies have dealt with whether or under which conditions the RH is truly used in paired-comparisons. However, even though the RH is a precise descriptive model, there has been less attention concerning the precision of the methods applied to measure RH-use. In the current work, I provide an overview of different measures of RH-use tailored to the paradigm of natural recognition which has emerged as a preferred way of studying the RH. The measures are compared with respect to different criteria --- with particular emphasis on how well they uncover true use of the RH. To this end, both simulations and a re-analysis of empirical data are presented. The results indicate that the adherence rate --- which has been pervasively applied to measure RH-use --- is a severely biased measure. As an alternative, a recently developed formal measurement model emerges as the recommended candidate for assessment of RH-use.
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Bibliographic InfoArticle provided by Society for Judgment and Decision Making in its journal Judgment and Decision Making.
Volume (Year): 5 (2010)
Issue (Month): 4 (July)
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recognition heuristic; methodology; simulation; adherence rate; signal detection theory; multinomial processing tree model.;
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