The statistical analysis of cheating paradigms

Abstract

One type of paradigm commonly used in studies on unethical behavior implements a lottery, relying on a randomization device to determine winnings while ensuring that the randomized outcome is only known to participants. Thereby, participants have the incentive and opportunity to cheat by anonymously claiming to have won. Data obtained in such a way are often analyzed using the observed “win” responses as a proxy for actual dishonesty. However, because the observed “win” response is contaminated by honest respondents who actually won, such an approach only allows for inferring dishonesty indirectly and leads to substantially underestimated effects. As a remedy, we outline approaches to estimate correlations between dishonesty and other variables, as well as to predict dishonesty in a modified logistic regression model. Using both simulated and empirical data, we demonstrate the superiority and relevance of the suggested methods.