This paper was presented as a Specially Invited Paper at the 19th Nordic Conference on Mathematical Statistics, Stockholm, June 2002 (NORDSTAT 2002).
Direct and Indirect Causal Effects via Potential Outcomes*
Article first published online: 19 MAY 2004
Scandinavian Journal of Statistics
Volume 31, Issue 2, pages 161–170, June 2004
How to Cite
Rubin, D. B. (2004), Direct and Indirect Causal Effects via Potential Outcomes. Scandinavian Journal of Statistics, 31: 161–170. doi: 10.1111/j.1467-9469.2004.02-123.x
- Issue published online: 19 MAY 2004
- Article first published online: 19 MAY 2004
- Received November 2002, in final form November 2003
- anthrax vaccine;
- causal inference;
- principal stratification;
- Rubin Causal Model;
- surrogate outcomes
Abstract. The use of the concept of ‘direct’ versus ‘indirect’ causal effects is common, not only in statistics but also in many areas of social and economic sciences. The related terms of ‘biomarkers’ and ‘surrogates’ are common in pharmacological and biomedical sciences. Sometimes this concept is represented by graphical displays of various kinds. The view here is that there is a great deal of imprecise discussion surrounding this topic and, moreover, that the most straightforward way to clarify the situation is by using potential outcomes to define causal effects. In particular, I suggest that the use of principal stratification is key to understanding the meaning of direct and indirect causal effects. A current study of anthrax vaccine will be used to illustrate ideas.