Some studies may be relatively representative of the intended study population at inception through rigorous efforts to ensure representative recruitment (e.g. birth cohort studies). However, as they mature the likelihood is that attrition from the study will be non-random, so that the cohort becomes less representative of the intended population as time goes on. Alternatively, the reverse may be true—the study may be unrepresentative at inception, but with low attrition. Selection bias can also occur if a sub-set of participants within a study is selected for more detailed investigation (e.g. genotyping) on the basis of having most data available or volunteering for further follow-up.2 There is already clear evidence from existing large-scale population studies that they are subject to a degree of selection bias. For example, higher genetic risk scores for schizophrenia are consistently associated with non-completion of questionnaires by study mothers and children, as well as non-attendance at data collection clinics, in the Avon Longitudinal Study of Parents and Children (ALSPAC)3 (see Box 1 The Avon Longitudinal Study of Parents and ChildrenBirth cohort studies are not immune to problems
