Abstract
The use of a proper study design is essential to the investigation of risk factors for disease or other outcomes. Observational studies are useful in studying risk factors for disease or clinical outcomes. Cohort and case–control study designs are the most common strategies used in observational research, with cross-sectional studies playing a less important role.
The choice between utilizing a cohort or case–control design depends upon several factors including disease prevalence and/or incidence, data availability and quality, and time required for follow-up. Confounding is a potentially serious problem that can affect the interpretation of either a cohort or a case–control study. Matching is a method used to reduce the effects of confounding. The degree of risk is quantified by the relative risk for cohort studies and the odds ratio for case–control studies. There are numerous sources of bias that can affect the interpretation of observational studies. In general, causality cannot be directly proven in observational studies, but certain criteria can suggest a causal hypothesis.
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Lesser, M.L. (2012). Design and Interpretation of Observational Studies: Cohort, Case–Control, and Cross-Sectional Designs. In: Supino, P., Borer, J. (eds) Principles of Research Methodology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3360-6_4
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DOI: https://doi.org/10.1007/978-1-4614-3360-6_4
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