Reader's guide to critical appraisal of cohort studies: 2. Assessing potential for confounding
Top Cited Papers
- 21 April 2005
- Vol. 330 (7497) , 960-962
- https://doi.org/10.1136/bmj.330.7497.960
Abstract
In cohort studies, who does or does not receive an intervention is determined by practice patterns, personal choice, or policy decisions. This raises the possibility that the intervention and comparison groups may differ in characteristics that affect the study outcome, a problem called selection bias. If these characteristics have independent effects on the observed outcome in each group, they will create differences in outcomes between the groups apart from those related to the interventions being assessed. This effect is known as confounding.1 In the first paper in the series we dealt with the design and use of cohort studies and how to identify selection bias.2 This paper focuses on the definition and assessment of confounders.Keywords
This publication has 15 references indexed in Scilit:
- Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confoundingBMJ, 2005
- Reader's guide to critical appraisal of cohort studies: 1. Role and designBMJ, 2005
- Association between falls in elderly women and chronic diseases and drug use: cross sectional studyBMJ, 2003
- Central Nervous System Active Medications and Risk for Fractures in Older WomenArchives of internal medicine (1960), 2003
- Walking and Leisure-Time Activity and Risk of Hip Fracture in Postmenopausal WomenJAMA, 2002
- Clinical Risk Factors for Hip Fracture in Elderly Women: A Case–Control StudyJournal of Orthopaedic Trauma, 2002
- Epidemiology of fallsAge and Ageing, 2001
- Statistics notes: Treatment allocation in controlled trials: why randomise?BMJ, 1999
- Estimating Causal Effects from Large Data Sets Using Propensity ScoresAnnals of Internal Medicine, 1997
- Risk Factors for Hip Fracture in White WomenNew England Journal of Medicine, 1995