Correlation is not Causation
DOI :
https://doi.org/10.29173/cjen312Résumé
In a recent news release, a link was announced between increased antibiotic use and the development of breast cancer (CBC staff, 2004). While researchers were careful in the article to reinforce that cause and effect have not been established, this was not clear in subsequent television and radio reports about the research. All too often, we hear of “links” or “associations” between variables and begin to consider this proof that one causes the other. Many health research studies involve testing for associations between variables and are referred to as correlational studies. Patients may bring in articles and ask about the studies, or we may be looking for information to support our practices. Either way, we need to be familiar with the meaning of studies discussing associations or links between variables. The purpose of this article is to explore the concept of correlation, describe correlational studies, and then to discuss the criteria required for establishing causation.Références
Brink, P.J., & Wood, M.J. (1998). Introduction (Chapter 1). In P.J. Brink, & M.J. Wood (Eds.), Advanced design in nursing research (2nd ed., pp. 3-20). Thousand Oaks: Sage.
Carter-Snell, C.J., & Sheehan, G. (1989). Comparison of two suction techniques for intubated ICU patients [Abstract]. Proceedings of the Twenty-eighth Interscience Conference on Antimicrobial Agents and Chemotherapy (p. 116).
CBC Staff. (2004). US Study suggests antibiotic, breast cancer link. CBC News. Retrieved February 20, 2004 from http://www.cbc.ca/stories/2004/02/16/antibiotic_bcancer040216
Cook, T.D., & Campbell, D.T. (1979). Causal inference and the language of experimentation. In T.D. Cook & D.T. Campbell (Eds.), Quasi-experimentation: Design & analysis issues for field settings. Boston: Houghton Mifflin Company.
Greenhalgh, T. (1998). Statistics for the nonstatistician - II: “Significant” relations and their pitfalls. Student BMJ, 6, 156-159.
Greeno, C.G. (2002). Major alternatives to the classic experimental design. Family Process, 41(4), 733-736.
Grimes, D.A., & Schulz, K.F. (2002). Descriptive studies: What they can and cannot do. Lancet, 359(9301), 145-149.
Linton, M. (2004, January 9). Nurses’ health study a landmark. C-Health, Toronto Sun. Retrieved March 3, 2004 from http://www.canoe.ca/Health0109/04_linton-sun.html
Loiselle, C.G., Profetto-McGrath, J., Polit, D.F., & Beck, C.T. (2004). Analyzing quantitative data. In C.G. Loiselle, J. Profetto-McGrath, D.F. Polit, & C.T. Beck (Eds.), Canadian Essentials of Nursing Research (pp. 329-380). Philadelphia: Lippincott.
Reynolds, C. (1999). Inferring causality from relational data and designs: Historical and contemporary lessons for research and clinical practice. The Clinical Neuropsychologist, 13(4), 385-395.
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