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SGR Modeling of Correlational Effects in Fake Good Self-report Measures

Author

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  • Luigi Lombardi

    (University of Trento)

  • Massimiliano Pastore

    (University of Padova)

  • Massimo Nucci

    (University of Padova)

  • Andrea Bobbio

    (University of Padova)

Abstract

In many self-report measures (i.e., personality survey items and diagnostic test items) the collected samples often include fake records. A case of particular interest in selfreport measures is the presence of caricature effects in participants’ responses under faking good motivation conditions. We say that a pattern of fake responses is a caricature pattern if it shows higher structural intercorrelations among faked items relative to the expected intercorrelations under the corresponding uncorrupted responses. In this paper we generalized a recent probabilistic perturbation procedure, called SGR - Sample Generation by Replacements - (Lombardi and Pastore (2012) Multivar Behav Res 47:519–546), to simulate caricature effects in fake good responses. To represent this particular faking behavior we proposed a novel extension of the SGR conditional replacement distribution which is based on a discrete version of the truncated multivariate normal distribution. We also applied the new procedure to real behavioral data on the role of perceived affective self-efficacy in social contexts and on self-report behaviors in reckless driving.

Suggested Citation

  • Luigi Lombardi & Massimiliano Pastore & Massimo Nucci & Andrea Bobbio, 2015. "SGR Modeling of Correlational Effects in Fake Good Self-report Measures," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 1037-1055, December.
    • Handle: RePEc:spr:metcap:v:17:y:2015:i:4:d:10.1007_s11009-014-9427-2
    DOI: 10.1007/s11009-014-9427-2
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    References listed on IDEAS

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    1. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    2. Massimiliano Pastore & Luigi Lombardi, 2014. "The impact of faking on Cronbach’s alpha for dichotomous and ordered rating scores," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1191-1211, May.
    3. Sik-Yum Lee & Wai-Yin Poon & P. Bentler, 1990. "A three-stage estimation procedure for structural equation models with polytomous variables," Psychometrika, Springer;The Psychometric Society, vol. 55(1), pages 45-51, March.
    4. Horrace, William C., 2005. "Some results on the multivariate truncated normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 209-221, May.
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    Cited by:

    1. Antonio Calcagnì & Luigi Lombardi, 2022. "Modeling random and non-random decision uncertainty in ratings data: a fuzzy beta model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 145-173, March.

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