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Front. Psychol. | doi: 10.3389/fpsyg.2018.01876

The effect of faking on the correlation between two ordinal variables: some population and Monte Carlo results.

  • 1Department of Psychology and Cognitive Science, University of Trento, Italy
  • 2Department of Data Analysis, Ghent University, Belgium

Correlational measures are probably the most spread statistical tools in psychological research. They are used by researchers to investigate, for example, relations between self-report measures usually collected using paper-pencil or online questionnaires. Like many other statistical analysis, also correlational measures can be seriously affected by specific sources of bias which constitute serious threats to the final observed results. In this contribution, we will focus on the impact of the fake data threat on the interpretation of statistical results for two well-know correlational measures (the Pearson product-moment correlation and the Spearman rank-order correlation). By using the Sample Generation by Replacement (SGR) approach, we analyze uncertainty in inferences based on possible fake data and evaluate the implications of fake data for correlational results. A population-level analysis and a Monte Carlo simulation are performed to study different modulations of faking on bivariate discrete variables with finite supports and varying sample sizes. We show that by using our paradigm it is always possible, under specific faking conditions, to increase (resp. decrease) the original correlation between two discrete variables in a predictable and systematic manner.

Keywords: Pearson correlation, Spearman correlation, Sample Generation by Replacement (SGR), Fake ordinal/discrete data, population analysis, Monte Carlo simulations.

Received: 19 Sep 2017; Accepted: 13 Sep 2018.

Edited by:

Holmes Finch, Ball State University, United States

Reviewed by:

Oi-Man Kwok, Texas A&M University, United States
Marjan Bakker, Tilburg University, Netherlands  

Copyright: © 2018 Bressan, Rosseel and Lombardi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Marco Bressan, University of Trento, Department of Psychology and Cognitive Science, Corso Bettini, 31 – Rovereto (TN), Trento, 38068, Trentino - Alto Adige, Italy,