Disentangling Qualitatively Different Faking Strategies in High-Stakes Personality Assessments: A Mixture Extension of the Multidimensional Nominal Response Model
Saved in:
| Title: | Disentangling Qualitatively Different Faking Strategies in High-Stakes Personality Assessments: A Mixture Extension of the Multidimensional Nominal Response Model |
|---|---|
| Language: | English |
| Authors: | Timo Seitz (ORCID |
| Source: | Educational and Psychological Measurement. 2025 85(6):1237-1277. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 41 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | High Stakes Tests, Personality Measures, Deception, Test Wiseness, Response Style (Tests), Testing Problems, Test Bias, Simulation |
| DOI: | 10.1177/00131644251341843 |
| ISSN: | 0013-1644 1552-3888 |
| Abstract: | High-stakes personality assessments are often compromised by faking, where test-takers distort their responses according to social desirability. Many previous models have accounted for faking by modeling an additional latent dimension that quantifies each test-taker's degree of faking. Such models assume a homogeneous response strategy among all test-takers, reflected in a measurement model in which substantive traits and faking jointly influence item responses. However, such a model will be misspecified if, for some test-takers, item responding is only a function of substantive traits or only a function of faking. To address this limitation, we propose a mixture modeling extension of the multidimensional nominal response model (M-MNRM) that can be used to account for qualitatively different response strategies and to model relationships of strategy use with external variables. In a simulation study, the M-MNRM exhibited good parameter recovery and high classification accuracy across multiple conditions. Analyses of three empirical high-stakes datasets provided evidence for the consistent presence of the specified latent classes in different personnel selection contexts, emphasizing the importance of accounting for such kind of response behavior heterogeneity in high-stakes assessment data. We end the article with a discussion of the model's utility for psychological measurement. |
| Abstractor: | As Provided |
| Entry Date: | 20260101 |
| Accession Number: | EJ1517636 |
| Database: | ERIC |
| Abstract: | High-stakes personality assessments are often compromised by faking, where test-takers distort their responses according to social desirability. Many previous models have accounted for faking by modeling an additional latent dimension that quantifies each test-taker's degree of faking. Such models assume a homogeneous response strategy among all test-takers, reflected in a measurement model in which substantive traits and faking jointly influence item responses. However, such a model will be misspecified if, for some test-takers, item responding is only a function of substantive traits or only a function of faking. To address this limitation, we propose a mixture modeling extension of the multidimensional nominal response model (M-MNRM) that can be used to account for qualitatively different response strategies and to model relationships of strategy use with external variables. In a simulation study, the M-MNRM exhibited good parameter recovery and high classification accuracy across multiple conditions. Analyses of three empirical high-stakes datasets provided evidence for the consistent presence of the specified latent classes in different personnel selection contexts, emphasizing the importance of accounting for such kind of response behavior heterogeneity in high-stakes assessment data. We end the article with a discussion of the model's utility for psychological measurement. |
|---|---|
| ISSN: | 0013-1644 1552-3888 |
| DOI: | 10.1177/00131644251341843 |
