Editing Recognition heuristic (section)

=== Measurement ===
One major criticism of studies on the recognition heuristic that was raised was that mere accordance with the recognition heuristic is not a good measure of its use. As an alternative, Hilbig et al. proposed to test the recognition heuristic more precisely devised a multinomial processing tree model for the recognition heuristic. A multinomial processing tree model is a simple statistical model often used in cognitive psychology for [[categorical variable|categorical data]].<ref>{{cite journal | last1 = Batchelder | first1 = W. H. | last2 = Riefer | first2 = D. M. | year = 1999 | title = Theoretical and empirical review of multinomial process tree modeling | journal = Psychonomic Bulletin & Review | volume = 6 | issue = 1| pages = 57–86 | doi = 10.3758/BF03210812 | pmid = 12199315 | doi-access = free }}</ref> Hilbig et al. claimed that a new model of recognition heuristic use was needed due to the confound between recognition and further knowledge. The multinomial processing tree model was shown to be effective and Hilbig et al. claimed that it provided an unbiased measure of the recognition heuristic.<ref name=Hilbig />

Pachur<ref name="Pachur 2011">{{cite journal|last=Pachur|first=T.|title=The limited value of precise tests of the recognition heuristic|journal=Judgment and Decision Making|date=2011 |volume=6|issue=5|pages=413–422|doi=10.1017/S1930297500001376 |url=http://journal.sjdm.org/11/rh21/rh21.html|access-date=2023-02-27|archive-date=2022-06-18|archive-url=https://web.archive.org/web/20220618075206/http://journal.sjdm.org/11/rh21/rh21.html|url-status=live|hdl=21.11116/0000-0002-1AA5-7|hdl-access=free}}</ref> stated that it is an imperfect model but currently it is still the best model to predict people’s recognition-based inferences. He believes that precise tests have a limited value basically because certain aspects of the recognition heuristic are often ignored and so the results could be inconsequential or misleading.