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One might say that the ultimate goal of any science is still to establish causal relations, even if classical “Laplacian” determinism has been somewhat jettisoned by theoretical physicists, which would imply that there may actually not be “true causes” to events (despite our continued attempts to assign them). Our search for them may be entirely misguided. Still, and a bit more down to earth, nothing suggests a stronger understanding of a scientific field than to be able to speak of causation about the phenomena it studies. However, more difficult than establishing causation in a given research paradigm is that of understanding what causation means in the first place. There exist several definitions of causality. Most definitions have at their core that causation is a relation between two events in which the second event is assumed to be a consequence, in some sense, of the first event.

For example, if I slip on a banana peel and fall, we might hypothesize that the banana peel caused my fall. However, was it the banana peel that caused my fall, or was it the worn out soles on my shoes that I was wearing that day that caused the fall? Had I been wearing mountain climbers instead of worn‐out running shoes, I might not have fallen. Who am I to say the innocent banana peel caused my fall? Causality is hard. Even if it seems that A caused B, there are usually many variables associated with the problem such that if adjusted or tweaked may threaten the causal claim. Some would say this is simply a trivial philosophical problem of specifying causality and it is “obvious” from the situation that the banana peel caused the fall. Nonetheless, it is clear from even such a simple example that causation is in no way an easy conclusion to draw. Perhaps this is also why it is extremely difficult to pinpoint true causes of virtually any behavior, natural or social. Hindsight is 20/20, but attributing causal attributes with any kind of methodological certainty in violent crimes, for instance, usually turns out to be speculative at best. True, we may accumulate evidence for prediction, but equating that with causation is under most circumstances the wish, not the reality, of a social theory.

In our brief discussion here we will not attempt to define causality. Books, dissertations, and treatises have been written exclusively on the topic. At most, what we can do in the amount of space we have is to simply heed the following advice to the reader—If you are going to speak of causation with regard to your research, be prepared to back up your theory of causation to your audience. It is simply not enough to say A causes B without subjecting yourself to at least some of the philosophical issues that accompany such a statement. Otherwise, it is strongly advised that you avoid words such as “cause” in hypothesizing or explaining results and findings. Relations and predictions are much epistemologically “safer” words to use, less prone to critique ending in quicksand. For a brief, but enlightening discussion of causality in the social sciences, see Fox (1997, pp. 3–14). For a more thorough treatment of the subject as it relates to structural equation models, see Mulaik (2009, pp. 63–117). Even a brief study of the philosophy of science goes a long way to understanding the complexities involved in using “causal” statements in research. These issues are not nearly as simple as they may at first appear.