Abstract
Within the field of clinical epidemiology bias is always a concern and the field is plagued by studies which have not taken this into account. Lack of insights in problems caused by confounding by indication, differential misclassification of exposure, differential misclassification of outcome, and selection bias have resulted in premature claims of causality. However, it is fair to say that during the last decade there has been a growing awareness of the problems, but it is still too easy to find many examples of a suboptimal study design where bias has led to wrong results.
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Olsen, J., Christensen, K., Murray, J., Ekbom, A. (2010). Sources of Error in Clinical Epidemiology. In: An Introduction to Epidemiology for Health Professionals. Springer Series on Epidemiology and Public Health, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1497-2_23
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DOI: https://doi.org/10.1007/978-1-4419-1497-2_23
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