Correlational models
Paul Christiansen · 2025
In this chapter, we will be discussing correlational designs. After reading the previous two chapters it is easy to think that we shouldn’t be using designs that cannot show causality. However, this is not the case, I will discuss the role of correlational designs when an experiment is impossible or impractical (drawing parallels with quasi-experiments). The chapter will go on to discuss the role of correlational designs with big data and how they are useful to study small, population level, effects that might not be visible in an experimental design but may have an impact on society as a whole. We will then briefly discuss how we can control for variables that may confound effects.