Why condition-based regression analysis (CRA) is indeed a valid test of self-enhancement effects: A response to Krueger et al. (2017)

How can the consequences of self-enhancement (SE) be tested empirically? Traditional two-step approaches for investigating SE effects have been criticized for providing systematically biased results. Recently, we suggested condition-based regression analysis (CRA) as an approach that enables users to test SE effects while overcoming the shortcomings of previous methods. Krueger et al. (2017) reiterated the problems of previous two-step approaches and criticized the extent to which CRA could solve these problems. However, their critique was based on a misrepresentation of our approach: Whereas a key element of CRA is the requirement that the coefficients of a multiple regression model must meet two conditions, Krueger et al.'s argumentation referred to the test of only a single condition. As a consequence, their reasoning does not allow any conclusions to be drawn about the validity of our approach. In this paper, we clarify these misunderstandings and explain why CRA is a valid approach for investigating the consequences of SE.