title: [Comparison of selected causality theories].
abstract: Different research traditions have separately developed various theories of causal inference. Three of these approaches are contrasted in this paper. In particular, I will explore differences and similarities of the potential outcomes approach, the generalized causal inference framework of Campbell, and the theory of causal DAGs. Each of the 3 approaches has strengths and weaknesses; however I argue that it is possible to combine them in applied research. The potential outcomes approach offers an exact and formal definition of a causal effect, however it is not very informative as to which covariates need to be selected for adjustment. The Campbell framework lacks a precise mathematical definition of a causal effect, but offers a long list of threats to internal validity that researchers can try to rule out in their studies. Causal DAGs offer applied researchers a tool to find minimally sufficient adjustment sets of covariates that allow an unbiased estimation of a causal effect, given that researchers are willing and able to encode their causal assumptions of all important covariates.
authors.affiliation: Institut für Erziehungswissenschaft, Abteilung Empirische Bildungsforschung und Pädagogische Psychologie, Universität Tübingen, Tübingen. felix.thoemmes@gmail.com
authors.forename: F
authors.initials: F
authors.lastname: Thoemmes
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D015984:Causality; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D015233:Models, Statistical