A bias in clinical research is a distortion of some sort that results in an error in the estimated size of a studied effect or association. It can arise because of a design problem, an interfering factor, or a judgment, any of which can affect the conception, design, or conduct of a study, or how outcome data are collected, analysed, interpreted, presented, or discussed. In 1979, after a symposium on case control studies, the clinical epidemiologist David Sackett published a proposal that a catalogue of bias should be constructed, covering biases that might “distort the design, execution, analysis, and interpretation of research.” In his paper he listed 56 types of biases, and since then others have published comparable lists. Combining those lists results in a total of about 150 different biases worthy of note, relevant to clinical interventional or observational studies or systematic reviews. Sackett died in 2015, since when, in his honour, members of Oxford’s Centre for Evidence Based Medicine (CEBM), a group that Sackett founded, have constructed a catalogue of biases, in which each entry adopts his proposed outline. The catalogue, which is freely available online, currently includes details of 67 different types of bias, giving definitions, examples, assessments of their impacts, and preventive measures. The Catalogue of Bias continues to grow, as more entries are added.