Measuring Reciprocal Dynamics between Communication Processes and Effects in Distinct Growth Sequences

Abstract

Over the last years, analyzing the dynamic reciprocal relationship between communication processes (i.e. mediated and interpersonal communication) and associated attitudes, beliefs, or behaviors has become more salient in communication research. However, methodological studies that focus on such communication dynamics are rare. In this paper, we present a model that tackles two statistical challenges of interrelated communication dynamics: (1) measuring the reciprocal relationship between communication processes and associated outcomes in distinct sequences and (2) the disaggregation of intraindividual and interindividual effects. To do so, we rely on latent growth models using structural equation modeling and extend them with a piecewise/spline regression approach. We refer to the combined model as the Sequential Latent Growth Model with Structured Residuals (SLGM-SR). Focusing on political communication as well as media effects and selection research, we present an empirical illustration and a modeling strategy by applying the model to short-term campaign panel data collected during the German federal elections in 2013. Further, we discuss (dis)-advantages of the sequential approach in the context of communication dynamics.