Dataset Information

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

ABSTRACT: How to detect faking on personality measures has been investigated using various methods and procedures. As previous findings are mixed and rarely based on ideal point item response theory models, additional research is needed for further exploration. This study modeled the responses of personality tests using ideal point method across instructed faking and honest responding conditions. A sample of undergraduate students participated the within-subjects measures to examine how the item location parameter derived from the generalized graded unfolding model changed, and how individuals' perception about items changed when faked. The mean test scores of faking group was positively correlated to the magnitude of within-subjects score change. The item-level analysis revealed both conscientiousness items (18.8%) and neuroticism items (50.0%) appeared significant shifts on item parameters, suggesting that response pattern changed from honest to faking conditions. The direction of the change appeared both in positive and negative way, demonstrating that faking could increase or decrease personality factor scores. The results indicated that the changes of perceptions on items could be operated by faking, offering some support for the ideal point model to be an adequate measure for detecting faking. However, the findings of diagnostic accuracy analysis also implied that the appropriateness of ideal point models for detecting faking should be under consideration, also be used with caution. Implications, further research directions, and limitations are discussed.

SUBMITTER: Liu J

PROVIDER: S-EPMC6987465 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

Liu Jie J Zhang Jinfu J

Frontiers in psychology 20200122

How to detect faking on personality measures has been investigated using various methods and procedures. As previous findings are mixed and rarely based on ideal point item response theory models, additional research is needed for further exploration. This study modeled the responses of personality tests using ideal point method across instructed faking and honest responding conditions. A sample of undergraduate students participated the within-subjects measures to examine how the item location ...[more]

PMID: 32038431

Similar Datasets

Project description:The meta-analytic finding that faking does not affect the criterion validity of self-report measures in applicant selection suggests cognitive abilities are crucial to fake personality to an expected optimal profile in self-report measures. Previous studies in this field typically focus on how the extent of faking changes self-report measurement. However, the effect of faking ability is rarely considered. In Study 1 (n = 151), we link two questionnaires, the WSQ and the NEO-PI-R, to use them for later faking ability tasks. With O∗NET expert ratings and the linked questionnaires, we establish veridical responses of optimal personality profiles for both questionnaires. Based on this, in Study 2, we develop six faking ability task employing both questionnaires and three common jobs to fake for. To score the tasks, we introduce profile similarity metrics that compare faked response vectors to optimal profile vectors. The faking ability tasks were administered to a community sample (n = 210) who additionally completed measures of cognitive abilities, namely general mental ability, crystallized intelligence, and interpersonal abilities. For all, based on previous research, it can be argued that they should predict individual differences in faking ability. We establish a measurement model of faking ability and its relation to the other cognitive abilities. Using structural equations modeling, we find the strongest effect for crystallized intelligence and weaker effects for general mental ability and interpersonal abilities, all positively predicting faking ability. We show for the first time that we can measure faking ability with psychometrically sound techniques, establish a confirmatory factor model of faking ability and that it is largely explained by other cognitive abilities. We conclude that research supporting a positive link between self-reported personality and job performance is presumably confounded by cognitive abilities, because they are predictive of both faking self-reported personality and job performance. We recommend researchers to broaden their measurements with assessments of faking ability or other cognitive abilities (besides general mental ability) in research regarding applicant selection.

Dataset Information

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

Publications

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets