Bias enters health studies at all stages and generally influences the magnitude and direction of the results. To obtain the least biased information, researchers must recognize the potential presence of biases and take steps to avoid and minimize their effects. Similarly, when evaluating study results, we should be aware of the different types of biases, their potential impact, and how this affects the interpretation and use of evidence in health decision-making. To better understand the persistent presence, diversity and impact of biases, we are compiling a Catalogue of Biases, resulting from the original work of David Sackett. The entries are a work in progress and describe a wide range of biases - describing their potential impact on research studies. Sackett recognized the importance of bias in research. His 1979 article, “Bias in analytic research,” published in the Journal of Chronic Diseases, reported the first draft of a 'catalogue of biases that can distort the design, execution, analysis and interpretation of research'. Sackett catalogued 35 biases that arise in sampling and measurement, in the context of clinical trials, and listed 56 biases that potentially affect case-control and cohort studies.