PubMed · 17093105
Statistical models for causation: what inferential leverage do they provide?
Abstract
Experiments offer more reliable evidence on causation than observational studies, which is not to gainsay the contribution to knowledge from observation. Experiments should be analyzed as experiments, not as observational studies. A simple comparison of rates might be just the right tool, with little value added by "sophisticated" models. This article discusses current models for causation, as applied to experimental and observational data. The intention-to-treat principle and the effect of treatment on the treated will also be discussed. Flaws in per-protocol and treatment-received estimates will be demonstrated.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
David A Freedman. 2006. Statistical models for causation: what inferential leverage do they provide?. https://doi.org/10.1177/0193841x06293771
Cite the original work for its findings. Save a collection to share your selection of sources.