Selection bias occurs when the sample used in a study or analysis is not representative of the population intended to be analysed. This bias can lead to incorrect conclusions and undermine the validity of the study.
Types :
- sampling bias - Occurs when certain members of the population are systematically more likely to be included in the sample than others. Eg, conducting a survey on internet usage by only sampling individuals in urban areas, excluding rural populations.
- self selection bias - happens when individuals select themselves into a group, causing a non-random sample.
- attrition bias - arises when participants drop out of a study over time in a non-random way.
- survivorship bias - Involves focusing on individuals or entities that survived a process and overlooking those that did not. Analysing the success strategies of only those companies that have survived over a long period, ignoring the companies that failed, which can lead to biased conclusions about the factors contributing to success.
- exclusion bias
- referral bias - A study on the effectiveness of a new treatment conducted at a specialised clinic, where patients are more likely to be referred if they have severe or complex cases, leading to an overrepresentation of severe cases in the sample.