An Introduction to Causal Inference

Publisher Website
Google Scholar
Abstract
Sociologists routinely employ regression analysis and a variety of related statistical models to draw causal inferences from survey data. Typically, the parameters of the models are interpreted as effects that indicate the change in a dependent variable that would occur if one or more independent variables were set to values other than the values actually taken. The purpose of this article is to formally demonstrate, in a fashion accessible to the social researcher who is not a methodologist, why the interpretations above do not generally hold, even when the model is correctly specified and a causal theory is given. Some implications for the way in which social research is and should be conducted are discussed. In particular, the usual strategies for testing competing causal explanations are misdirected. Further, the emphasis on causation in contemporary sociology is often misdirected.