@article{Marewski2010-06recog-28039,
  year={2010},
  doi={10.3758/PBR.17.3.287},
  title={From recognition to decisions : extending and testing recognition-based models for multialternative inference},
  number={3},
  volume={17},
  issn={1069-9384},
  journal={Psychonomic Bulletin & Review},
  pages={287--309},
  author={Marewski, Julian N. and Gaissmaier, Wolfgang and Schooler, Lael J. and Goldstein, Daniel G. and Gigerenzer, Gerd}
}

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    <dcterms:title>From recognition to decisions : extending and testing recognition-based models for multialternative inference</dcterms:title>
    <dcterms:bibliographicCitation>Psychonomic Bulletin &amp; Review ; 17 (2010), 3. - S. 287-309</dcterms:bibliographicCitation>
    <dcterms:abstract xml:lang="eng">The recognition heuristic is a noncompensatory strategy for inferring which of two alternatives, one recognized and the other not, scores higher on a criterion. According to it, such inferences are based solely on recognition. We generalize this heuristic to tasks with multiple alternatives, proposing a model of how people identify the consideration sets from which they make their final decisions. In doing so, we address concerns about the heuristic’s adequacy as a model of behavior: Past experiments have led several authors to conclude that there is no evidence for a noncompensatory use of recognition but clear evidence that recognition is integrated with other information. Surprisingly, however, in no study was this competing hypothesis - the compensatory integration of recognition - formally specified as a computational model. In four studies, we specify five competing models, conducting eight model comparisons. In these model comparisons, the recognition heuristic emerges as the best predictor of people’s inferences.</dcterms:abstract>
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    <dc:creator>Schooler, Lael J.</dc:creator>
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