Concepts of interaction.

@article{Rothman1980ConceptsOI,
  title={Concepts of interaction.},
  author={Kenneth J. Rothman and Sander Greenland and Alexander M. Walker},
  journal={American journal of epidemiology},
  year={1980},
  volume={112 4},
  pages={
          467-70
        }
}
Readers of the American Journal of Epidemiology have seen a lively discourse on the topic of synergy, a major conceptual area in epidemiology for which there exists fundamental controversy as to definitions. In 1974, one of us (KJR) (1) proposed that synergy (or its negative counterpart, antagonism) between two or more causes of disease ought to be evaluated in reference to a specific yardstick. The reference point was one that equated independence of the causes with the situation in which the… Expand

Topics from this paper

Invited commentary: the action in the interaction and exposure modification.
TLDR
It is argued successfully in this issue of the Journal that additive null models can capture pure forms of independent causal effects in studies of rare conditions and the concept of exposure modification, which characterizes most gene-environment interactions reported to date, is introduced. Expand
A competing risks approach to “biologic” interaction
TLDR
It is argued that sufficient cause interaction between two factors can be evaluated via the parameters in a particular statistical model, the additive hazard rate model, which is based on Rothman’s original discussion of sufficient causes. Expand
Interactions in Epidemiology: Relevance, Identification, and Estimation
TLDR
New results relating sufficient-cause models to regression models are provided and reinforce the point that concepts of biologic interaction do not in general correspond to the concept of statistical interaction, because the latter is only the need for a product term in a statistical model. Expand
Interaction on an Additive Scale
TLDR
It is recommended to report the separate effect of each exposure as well as the joint effect compared to the unexposed group as a joint reference category to permit evaluation of interaction on both an additive and multiplicative scale. Expand
Reporting of Interaction
Interaction is the situation whereby the association of one risk factor with a certain outcome variable differs across strata of another risk factor. From a public health perspective, the assessmentExpand
Interactions and Complexity: Goals and Limitations
We thank Morabia for his insightful commentary on the historical development of interaction analysis within epidemiology and on the ambiguous role interactions played in the development ofExpand
Mathematical modeling strategies for the analysis of epidemiologic research.
In the inaugural volume of the Annual Review of Public Health, Reuel Stallones suggested the following central axiom of epidemiology (27): "Disease does not distribute randomly in human populations."Expand
Elementary models for biological interaction
Abstract This paper provides a brief review of two theories of biological interaction of hazardous exposures, the Hewlett-Plackett theory and the sufficient-component cause theory. Although theExpand
When One Depends on the Other: Reporting of Interaction in Case-Control and Cohort Studies
TLDR
A survey of epidemiologic studies published in leading journals found that a majority of articles reporting cohort and case-control studies address possible interactions between exposures, but in about half of these, the information provided was unsatisfactory, and only 1 in 10 studies reported data that allowed readers to interpret interaction effects on an additive and multiplicative scale. Expand
The effect of joint exposures: examining the presence of interaction.
TLDR
Clinical epidemiological studies investigate whether an exposure, or risk factor, is causally related to the development or progression of a disease or mortality and whether this relation is different in different types of patients. Expand
...
1
2
3
4
5
...

References

SHOWING 1-4 OF 4 REFERENCES
Interaction in epidemiologic studies.
Synergism and interaction: are they equivalent?
Additive, multiplicative, and other models for disease risks.
Synergy and antagonism in cause-effect relationships.
  • K. Rothman
  • Medicine
  • American journal of epidemiology
  • 1974