Selectieuitval

Selectieuitval, also known as selection bias, is a type of bias that occurs when the selection of participants in a study is not random, leading to a sample that is not representative of the population. This can result in conclusions that are not generalizable to the broader population. Selection bias can arise from various sources, including self-selection, where individuals choose to participate based on their own preferences or characteristics, and non-response bias, where certain groups are less likely to respond to a survey or participate in a study.

There are several types of selection bias, including:

1. Volunteer bias: Participants who volunteer for a study may differ from those who do not, leading to a non-representative sample.

2. Healthy volunteer effect: In medical research, volunteers may be healthier than the general population, leading to biased results.

3. Attrition bias: Participants who drop out of a study may differ from those who complete it, affecting the representativeness of the sample.

4. Time interval bias: Studies that occur over a specific time period may not capture the full range of experiences or outcomes in the population.

To mitigate selection bias, researchers should aim to use random sampling techniques to ensure that the sample is representative of the population. Additionally, they should consider the potential sources of bias and take steps to address them, such as using propensity score matching or weighting techniques to adjust for differences between the sample and the population. By doing so, researchers can improve the validity and generalizability of their findings.