Year: 2025
Type: conference-paper
Abstract: Objective Present methods to detect and evaluate selection bias in epidemiologic studies. Methods In epidemiological studies, there is usually a target population to which we wish to draw inferences. The study is then conducted in a source population followed over a clearly defined period of time (the risk period). There is also a (perhaps smaller) study population, i.e. the group of people who actually take part in the study. Selection bias refers to differences between the source population and the study population. In cohort studies, important mechanisms for selection bias include non-response at baseline, loss-to-follow-up, left truncation, right truncation, and immortal person-time bias. In case-control studies, all of these biases are possible, but bias can also occur due to inappropriate selection of controls. Results Qualitative methods for assessing the existence, direction, and strength of selection bias, include the use of negative control exposures, negative control outcomes, ad hoc re-analyses of published data, comparisons with external data, and the use of multiple control groups. Quantitative methods also exist for sensitivity analyses in which ‘adjustments’ are made for hypothesized selection bias. Conclusions One of the primary questions posed to reviewers involved in an IARC Monograph is, ‘Can we reasonably rule out selection bias as an explanation for an observed exposure-cancer association?’ This can be particularly difficult to assess, since most published studies have little or no discussion of the potential for selection bias. It is therefore important that authors, and editors, are encouraged to report the information that is required for a valid assessment of the potential, direction and strength of possible selection bias.
Author: Neil Pearce
Institution: London School of Hygiene & Tropical Medicine
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414852791
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