Psychology Ph.D. Dissertations

A Structural Equation Modeling Approach to Predicting Applicant Faking

Date of Award


Document Type


Degree Name

Doctor of Philosophy (Ph.D.)



First Advisor

Margaret Brooks (Advisor)

Second Advisor

Scott Highhouse (Committee Member)

Third Advisor

William O'Brien (Committee Member)

Fourth Advisor

Yan Wu (Other)


Over the past few decades, applicant faking has become a topic of concern for many researchers and practitioners in the field of Industrial and Organizational Psychology. This has led to the development of many theoretical models of applicant faking. However, very few of these models have been tested empirically. The current study aims to address this need by empirically testing a parsimonious model of applicant faking. This model contains the most frequently-cited components of faking models (motivation to fake, ability to fake, individual differences related to faking, and situational influences). Faking was operationalized as the regression-adjusted difference scores between an “honest” administration of a personality test and an “applicant” condition of the same test. Motivation to fake was posited to mediate the relationship between individual differences and faking behavior. Situational influences were posited to moderate the relationships between individual differences and motivation to fake, while ability to fake was expected to moderate the relationship between motivation to fake and faking behavior. Structural equation modeling results demonstrated limited support for this model. The findings of this study highlight the need for faking researchers to focus on the measurement of faking. Implications for both theory and practice, as well as study limitations, are also discussed.