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Do sequential lineups impair underlying discriminability?


ABSTRACT: Debate regarding the best way to test and measure eyewitness memory has dominated the eyewitness literature for more than 30 years. We argue that resolution of this debate requires the development and application of appropriate measurement models. In this study we developed models of simultaneous and sequential lineup presentations and used these to compare these procedures in terms of underlying discriminability and response bias, thereby testing a key prediction of diagnostic feature detection theory, that underlying discriminability should be greater for simultaneous than for stopping-rule sequential lineups. We fit the models to the corpus of studies originally described by Palmer and Brewer (2012, Law and Human Behavior, 36(3), 247-255), to data from a new experiment and to eight recent studies comparing simultaneous and sequential lineups. We found that although responses tended to be more conservative for sequential lineups there was little or no difference in underlying discriminability between the two procedures. We discuss the implications of these results for the diagnostic feature detection theory and other kinds of sequential lineups used in current jurisdictions.

SUBMITTER: Kaesler M 

PROVIDER: S-EPMC7403381 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Do sequential lineups impair underlying discriminability?

Kaesler Matthew M   Dunn John C JC   Ransom Keith K   Semmler Carolyn C  

Cognitive research: principles and implications 20200804 1


Debate regarding the best way to test and measure eyewitness memory has dominated the eyewitness literature for more than 30 years. We argue that resolution of this debate requires the development and application of appropriate measurement models. In this study we developed models of simultaneous and sequential lineup presentations and used these to compare these procedures in terms of underlying discriminability and response bias, thereby testing a key prediction of diagnostic feature detection  ...[more]

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