Naive heuristics for paired comparisons: Some results on their relative accuracy

We study three heuristics for paired comparisons based on binary cues, which are all naive in that they ignore possible dependencies between cues, but take different approaches: linear (tallying) and lexicographic (Take The Best, Minimalist). There is empirical evidence on the heuristics' descriptive adequacy and some first results on their accuracy. We present new analytical results on their relative accuracy. When cues are independent given the values of the objects on the criterion, there exists a linear decision rule, equivalent to naive Bayes, which is optimal; we use this result to characterize the optimality of Take The Best and tallying. Also, tallying and Take The Best are more accurate than Minimalist. When cues are dependent and the number of cues and objects is psychologically plausible, Take The Best tends to be more accurate than tallying, but it is also possible that tallying, and Minimalist, are more accurate than Take The Best. (c) 2006 Elsevier Inc. All rights reserved.