error in selecting individuals or units for a sample, such that those units selected are not representative of the relevant population. For example, a medical researcher who studies a sample of patients that omits certain types of people who have the disorder of interest is likely to obtain results having an ascertainment bias. The term is often preferred over sampling bias in clinical contexts.