Options
IAT Faking Indices Revisited : Aspects of Replicability and Differential Validity (Poster)
Röhner, Jessica; Holden, Ronald R.; Schütz, Astrid (2022): IAT Faking Indices Revisited : Aspects of Replicability and Differential Validity (Poster), in: Abstracts of the Psychonomic Society, Bamberg: Otto-Friedrich-Universität, doi: 10.20378/irb-56855.
Faculty/Chair:
Author:
Title of the compilation:
Abstracts of the Psychonomic Society
Conference:
Psychonomic Society 63rd Annual Meeting, November 17-20, 2022 ; Boston, Massachusetts, USA
Publisher Information:
Year of publication:
2022
Pages:
Language:
English
Remark:
Als Zeitschriftenartikel erschienen in: Behavior research methods : BRM. (2022), Online First. - DOI: 10.3758/s13428-022-01845-0.
Siehe auch FIS-Eintrag: https://fis.uni-bamberg.de/handle/uniba/54527
Siehe auch FIS-Eintrag: https://fis.uni-bamberg.de/handle/uniba/54527
DOI:
Abstract:
Indices [slowing, speeding, increasing or reducing errors in congruent or incongruent blocks; Combined Task Slowing (CTS); Ratio 150-10000] allegedly detect faking in IATs, however, studies on these are inconclusive and statistically underpowered. Also, results’ stability, indices’ unique predictivity, combining indices, and variations in computing faking success remain unexplored. We reanalyzed a large sample (N = 750) completing an extraversion IAT, finding that faking strategies depend on the direction of faking. Successful faking of low scores was detected from slowing down on the congruent block, and less with CTS. Successful faking of high scores was detected from slowing down and increasing errors on the incongruent block, and with CTS. Results demonstrated stability across subsamples and different computations of faking success. Increasing errors had the strongest impact on the classification. Apparently, fakers use goal-dependent strategies which are not all successful. To detect faking, we recommend combining indices and considering the context.
GND Keywords: ; ;
Implicit Association Test
Manipulation
Testergebnis
Keywords: ; ; ;
faking
faking detection
Implicit Association Test (IAT)
Replication
DDC Classification:
RVK Classification:
Type:
Conferenceobject
Activation date:
January 10, 2023
Permalink
https://fis.uni-bamberg.de/handle/uniba/56855