Deconfounding confounding part 1: traditional explanations

The first article of this series1 presented a framework to assist in judging the presence of bias:

1 Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, Newcastle, NSW
2 John Hunter Hospital, Newcastle, NSW
3 Macquarie University, Sydney, NSW

Correspondence: john.attia@newcastle.edu.au

Competing interests:

No relevant disclosures.

1. Attia JR, Jones MP, Suthers B. Aiming for the truth: understanding the difference between validity and precision. Med J Aust 2016; 205: 392-394. <MJA full text>
2. Lipsitch M, Tchetgen Tchetgen E, Cohen T. Negative controls: a tool for detecting confounding and bias in observational studies. Epidemiology 2010; 21: 383-388.
3. Rossouw JE, Anderson GL, Prentice RL, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women’s Health Initiative randomized controlled trial. JAMA 2002; 288: 321-333.
4. Attia J, Page J. A graphic framework for teaching critical appraisal of randomised controlled trials. Evid Based Med 2001; 6: 68-69.

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