Jimmy Calanchini

University of California
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Articles (9)

Implicit measures were initially assumed to assess stable individual differences, but other perspectives posit that they reflect context-dependent processes. This pre-registered research investigates whether the processes contributing to responses on the race Implicit Association Test are temporally stable and reliably measured using multinomial processing tree modeling. We applied two models—the Quad model and the Process Dissociation Procedure—to six datasets ( N = 2,036), each collected over two occasions, examined the within-measurement reliability and between-measurement stability of model parameters, and meta-analyzed the results. Parameters reflecting accuracy-oriented processes demonstrate adequate stability and reliability, which suggests these processes are relatively stable within individuals. Parameters reflecting evaluative associations demonstrate poor stability but modest reliability, which suggests that associations are either context-dependent or stable but noisily measured. These findings suggest that processes contributing to racial bias on implicit measures differ in temporal stability, which has practical implications for predicting behavior using the Implicit Association Test.

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2023

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2023

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2023

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2023

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2022

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2021

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2021

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2021

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2021

Collaborators (3)

Iniobong Essien

Leuphana University of Lüneburg

GERMANY
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Oliver Christ

Full Professor

FernUniversität in Hagen

GERMANY
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Jeffrey Sherman

Professor

University of California, Davis

UNITED STATES
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