Sarah Humberg

Enhanced Versus Simply Positive: A New Condition-Based Regression Analysis to Disentangle Effects of Self-Enhancement From Effects of Positivity of Self-View

Despite a large body of literature and ongoing refinements of analytical techniques, research on the consequences of self-enhancement (SE) is still vague about how to define SE effects, and empirical results are inconsistent. In this paper, we point out that part of this confusion is due to a lack of conceptual and methodological differentiation between effects of individual differences in how much people enhance themselves (SE) and in how positively they view themselves (positivity of self-view; PSV). We show that methods commonly used to analyze SE effects are biased because they cannot differentiate between the effects of PSV and the effects of SE. We provide a new condition-based regression analysis (CRA) that unequivocally identifies effects of SE by testing intuitive and mathematically derived conditions on the coefficients in a bivariate linear regression. Using data from 3 studies on intellectual SE (total N = 566), we then illustrate that the CRA provides novel results as compared with traditional methods. Results suggest that many previously identified SE effects are in fact effects of PSV alone. The new CRA approach thus provides a clear and unbiased understanding of the consequences of SE. It can be applied to all conceptualizations of SE and, more generally, to every context in which the effects of the discrepancy between 2 variables on a third variable are examined.

Response Surface Analysis in Personality and Social Psychology: Checklist and Clarifications for the Case of Congruence Hypotheses

Response surface analysis (RSA) enables researchers to test complex psychological effects, for example, whether the congruence of two psychological constructs is associated with higher values in an outcome variable. RSA is increasingly applied in the personality and social psychological literature, but the validity of published results has been challenged by some persistent oversimplifications and misconceptions. Here, we describe the mathematical fundamentals required to interpret RSA results, and we provide a checklist for correctly identifying congruence effects. We clarify two prominent fallacies by showing that the test of a single RSA parameter cannot indicate a congruence effect, and when there is a congruence effect, RSA cannot indicate whether a predictor mismatch in one direction (e.g., overestimation of one’s intelligence) is better or worse than a mismatch in the other direction (underestimation). We hope that this contribution will further enhance the validity and strength of empirical studies that apply this powerful approach.

Is Accurate, Positive, or Inflated Self-Perception Most Advantageous for Psychological Adjustment? A Competitive Test of Key Hypotheses

Empirical research on the (mal-)adaptiveness of favorable self-perceptions, self-enhancement, and self-knowledge has typically applied a classical null-hypothesis testing approach and provided mixed and even contradictory findings. Using data from 5 studies (laboratory and field, total N = 2,823), we used an information-theoretic approach combined with Response Surface Analysis to provide the first competitive test of 6 popular hypotheses: that more favorable self-perceptions are adaptive versus maladaptive (Hypotheses 1 and 2: Positivity of self-view hypotheses), that higher levels of self-enhancement (i.e., a higher discrepancy of self-viewed and objectively assessed ability) are adaptive versus maladaptive (Hypotheses 3 and 4: Self-enhancement hypotheses), that accurate self-perceptions are adaptive (Hypothesis 5: Self-knowledge hypothesis), and that a slight degree of self-enhancement is adaptive (Hypothesis 6: Optimal margin hypothesis). We considered self-perceptions and objective ability measures in two content domains (reasoning ability, vocabulary knowledge) and investigated 6 indicators of intra- and interpersonal psychological adjustment. Results showed that most adjustment indicators were best predicted by the positivity of self-perceptions. There were some specific self-enhancement effects, and evidence generally spoke against the self-knowledge and optimal margin hypotheses. Our results highlight the need for comprehensive and simultaneous tests of competing hypotheses. Implications for the understanding of underlying processes are discussed.

Testing Similarity Effects with Dyadic Response Surface Analysis: Dyadic response surface analysis

Dyadic similarity effect hypotheses state that the (dis)similarity between dyad members (e.g. the similarity on a personality dimension) is related to a dyadic outcome variable (e.g. the relationship satisfaction of both partners). Typically, these hypotheses have been investigated by using difference scores or other profile similarity indices as predictors of the outcome variables. These approaches, however, have been vigorously criticized for their conceptual and statistical shortcomings. Here, we introduce a statistical method that is based on polynomial regression and addresses most of these shortcomings: dyadic response surface analysis. This model is tailored for similarity effect hypotheses and fully accounts for the dyadic nature of relationship data. Furthermore, we provide a tutorial with an illustrative example and reproducible R and Mplus scripts that should assist substantive researchers in precisely formulating, testing, and interpreting their dyadic similarity effect hypotheses.