Detecting Response Styles and Faking in Personality and Organizational Assessments by Mixed Rasch Models

  • Michael Eid
  • Michael J. Zickar
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)


Mixture IRT models such as the mixed Rasch model (RM) have the potential to illuminate conflicting findings in the analysis of responses to organizational assessments of noncognitive abilities such as personality inventories and attitude assessments. The preponderance of psychometric work (especially in the early history of test analysis) has been done in the realm of cognitive abilities, where data are presumably much more ordered than in the personality or noncognitive ability domains (see Zickar, 2001). One key difference between personality and ability assessment is that in personality measurement, respondents often know what the “correct” or socially desirable answer is even if that answer does not apply to their own personality. Given this, responses to personality items depend not only on the respondent’s true personality but also his or her motivation to respond favorably (or unfavorably in certain situations). This can create problems because in a given sample of job applicants there may be a diversity of faking styles present. Some or most respondents may reply honestly out of ethical or religious reasons or for fear of getting caught. Other respondents may feel no compunction about distorting and will choose answers that they believe will result in their best chance of being hired. Finally, others, perhaps worried about getting caught but still motivated to get hired, might slightly exaggerate their personality characteristics to increase their chances of being hired.


Latent Class Social Orientation Latent Trait Class Membership Item Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  • Michael Eid
    • 1
  • Michael J. Zickar
    • 2
  1. 1.Free University of BerlinBerlinUSA
  2. 2.Bowling Green State UniversityBowling GreenGermany

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