This course will explore the concept of selection bias and how it can lead to unfair outcomes. We will discuss the different types of selection bias and how to recognize them. We will also look at strategies to avoid selection bias, such as using random selection processes
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that the association between exposure and outcome among those selected for analysis differs from the association among those eligible. It typically occurs when researchers condition on a factor that is influenced both by the exposure and the outcome, creating a false association between them. Selection bias encompasses several forms of bias, including differential loss-to-follow-up, incidence–prevalence bias, volunteer bias, healthy-worker bias, and nonresponse bias.