Literature DB >> 22545617

Mixing strong and weak targets provides no evidence against the unequal-variance explanation of ʐROC slope: a comment on Koen and Yonelinas (2010).

Jeffrey J Starns1, Caren M Rotello, Roger Ratcliff.   

Abstract

Koen and Yonelinas (2010; K&Y) reported that mixing classes of targets that had short (weak) or long (strong) study times had no impact on ʐROC slope, contradicting the predictions of the encoding variability hypothesis. We show that they actually derived their predictions from a mixture unequal-variance signal detection (UVSD) model, which assumes 2 discrete levels of strength instead of the continuous variation in learning effectiveness proposed by the encoding variability hypothesis. We demonstrated that the mixture UVSD model predicts an effect of strength mixing only when there is a large performance difference between strong and weak targets, and the strength effect observed by K&Y was too small to produce a mixing effect. Moreover, we re-analyzed their experiment along with another experiment that manipulated the strength of target items. The mixture UVSD model closely predicted the empirical mixed slopes from both experiments. The apparent misfits reported by K&Y arose because they calculated the observed slopes using the actual range of ʐ-transformed false-alarm rates in the data, but they computed the predicted slopes using an extended range from - 5 to 5. Because the mixed predictions follow a slightly curved ʐROC function, different ranges of scores have different linear slopes. We used the actual range in the data to compute both the observed and predicted slopes, and this eliminated the apparent deviation between them. (c) 2012 APA, all rights reserved.

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Year:  2012        PMID: 22545617     DOI: 10.1037/a0027040

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  8 in total

1.  Validating the unequal-variance assumption in recognition memory using response time distributions instead of ROC functions: A diffusion model analysis.

Authors:  Jeffrey J Starns; Roger Ratcliff
Journal:  J Mem Lang       Date:  2014-01       Impact factor: 3.059

2.  Variation in the standard deviation of the lure rating distribution: Implications for estimates of recollection probability.

Authors:  Stephen Dopkins; Kaitlin Varner; Darin Hoyer
Journal:  Psychon Bull Rev       Date:  2017-10

3.  Examining the causes of memory strength variability: recollection, attention failure, or encoding variability?

Authors:  Joshua D Koen; Mariam Aly; Wei-Chun Wang; Andrew P Yonelinas
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2013-07-08       Impact factor: 3.051

4.  Still no evidence for the encoding variability hypothesis: a reply to Jang, Mickes, and Wixted (2012) and Starns, Rotello, and Ratcliff (2012).

Authors:  Joshua D Koen; Andrew P Yonelinas
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2013-01       Impact factor: 3.051

5.  Unequal-strength source zROC slopes reflect criteria placement and not (necessarily) memory processes.

Authors:  Jeffrey J Starns; Angela M Pazzaglia; Caren M Rotello; Michael J Hautus; Neil A Macmillan
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2013-04-08       Impact factor: 3.051

6.  Paying attention to attention in recognition memory: insights from models and electrophysiology.

Authors:  Chad Dubé; Lisa Payne; Robert Sekuler; Caren M Rotello
Journal:  Psychol Sci       Date:  2013-10-01

7.  A novel approach to an old problem: analysis of systematic errors in two models of recognition memory.

Authors:  Adam J O Dede; Larry R Squire; John T Wixted
Journal:  Neuropsychologia       Date:  2013-10-29       Impact factor: 3.139

8.  The unequal variance signal-detection model of recognition memory: Investigating the encoding variability hypothesis.

Authors:  Rory W Spanton; Christopher J Berry
Journal:  Q J Exp Psychol (Hove)       Date:  2020-02-27       Impact factor: 2.143

  8 in total

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