Causation

About: Causation is a research topic. Over the lifetime, 6775 publications have been published within this topic receiving 166878 citations.

The environment and disease: association or causation?

Abstract: In 1965, Austin Bradford Hill published the article "The Environment and Disease: Association or Causation?" in the Proceedings of the Royal Society of Medicine. In the article, Hill describes nine criteria to determine if an environmental factor, especially a condition or hazard in a work environment, causes an illness. The article arose from an inaugural presidential address Hill gave at the 1965 meeting of the Section of Occupational Medicine of the Royal Society of Medicine in London, England. The criteria he established in the article became known as the Bradford Hill criteria and the medical community refers to them when determining whether an environmental condition causes an illness. The criteria outlined in "The Environment and Disease: Association or Causation?" help identify the causes of many diseases, including cancers of the reproductive system.

The environment and disease: association or causation?

Abstract: In 1965, Sir Austin Bradford Hill offered his thoughts on: “What aspects of [an] association should we especially consider before deciding that the most likely interpretation of it is causation?” He proposed nine means for reasoning about the association, which he named as: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. In this paper, we look at what motivated Bradford Hill to propose we focus on these nine features. We contrast Bradford Hill’s approach with a currently fashionable framework for reasoning about statistical associations – the Common Task Framework. And then suggest why following Bradford Hill, 50+ years on, is still extraordinarily reasonable.

Statistics and Causal Inference

Abstract: Problems involving causal inference have dogged at the heels of statistics since its earliest days. Correlation does not imply causation, and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is addressed by using a particular model for causal inference (Holland and Rubin 1983; Rubin 1974) to critique the discussions of other writers on causation and causal inference. These include selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modeling.

Causation and Effectuation: Toward a Theoretical Shift from Economic Inevitability to Entrepreneurial Contingency

Abstract: In economics and management theories, scholars have traditionally assumed the existence of artifacts such as firms/organizations and markets. I argue that an explanation for the creation of such artifacts requires the notion of effectuation. Causation rests on a logic of prediction, effectuation on the logic of control. I illustrate effectuation through business examples and realistic thought experiments, examine its connections with existing theories and empirical evidence, and offer a list of testable propositions for future empirical work.