Confounding and Simpson’s paradox

Abstract

A common problem when analysing clinical data is that of confounding. This occurs when the association between an exposure and an outcome is investigated but the exposure and outcome are strongly associated with a third variable. An extreme example of this is Simpson’s paradox, in which this third factor reverses the effect first observed.1 This phenomenon has long been recognised as a theoretical possibility but few real examples have been presented.

Reference

SA Julious, MA Mullee “Confounding and Simpson’s paradox” (1994) DOI: 10.1136/bmj.309.6967.1480

@Article{julious1994,
  title = {Confounding and Simpson’s paradox},
  abstract = {A common problem when analysing clinical data is that of confounding. This occurs when the association between an exposure and an outcome is investigated but the exposure and outcome are strongly associated with a third variable. An extreme example of this is Simpson's paradox, in which this third factor reverses the effect first observed.1 This phenomenon has long been recognised as a theoretical possibility but few real examples have been presented.},
  volume = {309},
  issn = {1468-5833},
  url = {http://dx.doi.org/10.1136/bmj.309.6967.1480},
  doi = {10.1136/bmj.309.6967.1480},
  number = {6967},
  journal = {BMJ},
  publisher = {BMJ},
  author = {Julious, SA and Mullee, MA},
  year = {1994},
  month = {dec},
  pages = {1480–1481},
  custom-url-pdf = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2541623/pdf/bmj00468-0032.pdf}
}