How to Capture Reciprocal Communication Dynamics: Comparing Longitudinal Statistical Approaches in Order to Analyze Within- and Between-Person Effects

Abstract

Choosing an appropriate statistical model to analyze reciprocal relations between individuals’ attitudes, beliefs, or behaviors over time can be challenging. Often, decisions for or against specific models are rather implicit and it remains unclear whether the statistical approach fits the theory of interest. For longitudinal models, this is problematic since within- and between-person processes can be confounded leading to wrong conclusions. Taking the perspective of the reinforcing spirals model (RSM) focusing on media effects and selection, we compare six statistical models that were recently used to analyze the RSM and show their ability to separate within- and between-person components. Using empirical data capturing respondents’ development during adolescence, we show that results vary across statistical models. Further, Monte Carlo simulations indicate that some approaches might lead to wrong conclusions if specific communication dynamics are present. In sum, we recommend using approaches that explicitly model and clearly separate within- and between-person effects.

Maintenance or change? Examining the reinforcing spiral between social media news use and populist attitudes

“…Finally, respondents might not have perceived any salient trigger that elicited a threat to populist attitudes (Slater, 2007). It is therefore our recommendation that future research applies the novel methodological and analytical framework presented hererelying on the reinforcing spirals model (Slater, 2007;2015; and the latent curve models with structured residuals (Curran et al, 2014;Thomas et al, 2021) to replicate these findings in a different setting where such trigger events are manipulated or levels of perceived threat are measured.…”

“…As a result, the conceptual clarity of the measure is diluted, reflecting hard news as well as interpersonal communication. A more nuanced measure of social media use, as well as detailed media diaries and mobile intensive longitudinal linkage analysis (Thomas et al, 2021), could provide future research with relevant insights to address the aforementioned concerns. Last but not least, one should keep in mind, that our samples are not representative of the German population.…”

“…Reinforcing spirals are described and analyzed as an intra-individual (within-person) process taking into account person-specific or contextual factors at an inter-individual (between-person) level simultaneously (Moeller et al, 2018;Thomas, Shehata, Otto, Möller, & Prestele, 2021). To model reinforcing spirals, intra-individual and inter-individual effects must be separated.…”

“…The autoregressive and cross-lagged residual structure can be understood as the state-like component of the model, as residuals fluctuate between waves and reflect within-person variability. Double-sided mediations of social media news use mediating auto-regressive relations between populist attitudes and vice versa (Slater, 2015), are defined at an intra-individual level as well (Thomas et al, 2021).…”

Digital Well-Being Theory and Research

“…This reverses the above assumed causal process and empirically, it implies a negative correlation between sharing and connectedness. This shows that even for a seemingly simple bivariate relationship, the explanatory mechanisms require much precision often lacking (Thomas et al, 2021) (see example in Fig. 3; replication code).…”