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Deconfounding confounding part 3: controlling for confounding in statistical analyses

Alice M Richardson and Grace Joshy
Med J Aust 2020; 213 (5): . || doi: 10.5694/mja2.50737
Published online: 7 September 2020

The traditional concept of confounding was previously introduced in this Key Research Skills series — a confounder is a variable that is associated with both the exposure and outcome of interest without being an intermediate on the causal pathway between them.1 Although the earlier article also outlined how a randomised controlled trial (RCT) can be used as a solution to handle confounding at the study design phase, it is not always feasible to use an RCT. For example, consider a study looking at the association between smoking (exposure) and cardiovascular disease (CVD; outcome). It is not ethical to randomly assign people to smoke! The alternative is to conduct an observational study in which confounders are carefully identified, measured without too much error, and adjusted for in the statistical analysis.

  • Alice M Richardson1
  • Grace Joshy2

  • 1 Statistical Consulting Unit, Australian National University, Canberra, ACT
  • 2 National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT

Correspondence: Alice.Richardson@anu.edu.au


Series editors

John R Attia

Michael P Jones


Competing interests:

No relevant disclosures.

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