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

Luigi Lombardi (), Massimiliano Pastore (), Massimo Nucci () and Andrea Bobbio ()
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Luigi Lombardi: University of Trento
Massimiliano Pastore: University of Padova
Massimo Nucci: University of Padova
Andrea Bobbio: University of Padova

Methodology and Computing in Applied Probability, 2015, vol. 17, issue 4, 1037-1055

Abstract: 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.

Keywords: Sample generation by replacement; Fake-good data; Truncated multivariate normal distribution; Correlational structures; Caricature effect; C15; C34; C46; C63 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11009-014-9427-2

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