Aligning Media Effects Theories With Empirical Evaluation Using Informative Hypotheses

Theories, hypotheses, and their empirical evaluation are usually misaligned in media effects research. While the field focuses on directional effects of substantial magnitude, they are typically examined with null hypothesis significance testing (NHST), which does not support direct inference concerning these hypotheses. This tutorial encourages researchers to adopt informative hypothesis evaluation with an Akaike information criterion (AIC)-type criterion called GORIC(A). Throughout four empirical examples using simulated data, the tutorial highlights the strengths of informative hypotheses with GORIC(A) compared to the NHST, including advanced techniques like minimum-effect testing. Specifically, the tutorial facilitates inference for effects central to media effects theories and research: moderated, mediated, and transactional (bidirectional). Informative hypothesis evaluation and GORIC(A) are presented as powerful tools to evaluate expectations that align closely with researchers' theories. Aligning inference procedures with theories is needed for well-informed and meaningful theory-building in media effects research and beyond.