How to Test Questions About Similarity in Personality and Social Psychology Research

Abstract

Social and personality psychologists are often interested in the extent to which similarity, agreement, or matching matters. The current article describes response surface analysis (RSA), an approach designed to answer questions about how (mis)matching predictors relate to outcomes while avoiding many of the statistical limitations of alternative, often-used approaches. We explain how RSA provides compressive and often more valid answers to questions about (mis)matching predictors than traditional approaches provide, outline steps on how to use RSA (including modifiable syntax), and demonstrate how to interpret RSA output with an example. To bolster our argument that RSA overcomes many limitations of traditional approaches (i.e., incomplete or misleading inferences), we compare results from four popular approaches (i.e., difference scores, residuals, moderated regression, and the truth and bias model) to those obtained from RSA. We discuss specific applications of RSA to social and personality psychology research.

Relationship satisfaction and similarity of personality traits, personal values, and attitudes

“…analysis followed by response surface analysis (RSA) was used for examining the associations between relationship satisfaction and couples' dyadic combinations of each characteristic (Barranti et al, 2017;Edwards, 2002). The procedure closely followed that used by .…”

Self–other personality agreement and internalizing problems in adolescence

“…Past research on self–other agreement has typically relied on methods that may produce inaccurate or incomplete results regarding the implications of self–other agreement at different levels of the personality measures such as difference scores or regression residuals (cf. Barranti, Carlson, & Côté, ). The purpose of the present study was to address this and other limitations of past approaches by examining the degree to which self–other personality agreement is associated with internalizing problems in adolescence, using response surface analysis (RSA) and 1‐year longitudinal data from 570 Dutch adolescents and their parents, siblings, and friends.…”

“…Recently, studies in personality and social psychology have begun to use polynomial regression in combination with RSA to address questions about the implications of congruence versus incongruence in personality ratings (e.g., Bleidorn et al, ; Denissen et al, ; Franken, Laceulle, van Aken, & Ormel, ; van Scheppingen, Chopik, Bleidorn, & Dennisen, ). RSA provides more accurate answers to more nuanced questions by assessing different forms of self–other (dis)agreement (e.g., congruently positive vs. congruently negative views) while reducing statistical biases and interpretation problems associated with traditional approaches (Barranti et al, ; Edwards & Parry, ; Shanock, Baran, Gentry, Pattison, & Heggestad, ).…”

Self-enhancement: Conceptualization and Assessment

“…In other words, it cannot be said that happiness is predicted by the positivity of the self-image, S, the person's true score, T, and the discrepancy between S and T. The latter term is redundant, and as we argue, problematic when reified. There is, however, the possibility that the statistical interaction between S and T or polynomial transforms of each might explain additional variance (Barranti, Carlson, & Côté, 2017), but the relevance of these predictors for the theoretical construct of self-enhancement remains open to debate (Edwards, 1994;Krueger & Wright, 2011;Leising, Locke, Kurzius, & Zimmermann, 2016;Zuckerman & Knee, 1995). 1 Other concerns are that discrepancy scores lack reliability when true variability is low (Lord, 1958;Rogosa & Willett, 1983) and that they fall on arbitrary metrics that obscure "where a given score locates an individual on the underlying psychological dimension" (Blanton & Jaccard, 2006, p. 27).…”

“…Extending pioneering work by Edwards (1994), Barranti et al (2017) proposed Response Surface Analysis (RSA) as a general solution for research questions conventionally addressed with discrepancy scores. Applied to selfenhancement, RSA regresses a criterion variable H on two predictors S and T as well their interaction S x T and the nonlinear transforms S 2 and T 2 , but does so only if the inclusion of the latter three predictors yields a statistically significant increase in the explained variance, R 2 .…”