What Is Self-Selection Bias? | Definition & Example
Self-selection bias (also called volunteer bias) refers to the bias that can occur when individuals are allowed to choose whether they want to participate in a research study. Because participants often differ from nonparticipants in ways significant to the research, self-selection can lead to a biased sample and affects the generalisability of your results.
Because of that, students who either strongly enjoyed or hated the books are more likely to fill in the survey. Students who didn’t feel strongly about the books are less likely to participate in the survey.
As a result, your sample will comprise mostly those with strong opinions and will not be representative of all students. By allowing students to choose whether to participate, you have allowed self-selection bias to occur.
What is self-selection bias?
Self-selection bias refers to the systematic, nonrandom difference in characteristics between individuals who choose to participate in a study and those who don’t.
Studies have shown that individuals who volunteer to respond to surveys tend to be better educated, have higher socioeconomic status, and lead more active lives than those who don’t. Additionally, individuals who are personally interested in a certain topic are more likely to participate in a research study about it.
Self-selection bias occurs when participants differ in some way from nonparticipants. This makes your sample unrepresentative of your population of interest. It also threatens the external validity of your findings – your ability to make generalisations from your sample to the target population.
When a sample contains only participants willing to participate in the survey or experiments, self-selection bias will heavily affect the results.
Self-selection bias example
Non-probability samples, including self-selected or volunteer samples, run the risk of containing too many engaged people, or only containing those with the strongest opinions.
However, these surveys suffer from self-selection bias, because those who feel animated enough by the topic to participate are more likely to do so.
Additionally, it is very challenging to verify that respondents really belong to the intended population. For example, there is no way to easily verify whether respondents to a social media poll about parenting are actually parents.
As a result, these polls tend to overrepresent individuals who have strong opinions, and they are unlikely to accurately reflect public opinion – even with a sample size in the thousands.
How to avoid self-selection bias
Although it’s not always possible to completely eliminate self-selection bias, there are steps you can take to minimise its impact on your findings.
- When conducting experimental research, make sure you use random assignment. This way, every member of the sample has a known or equal chance of being placed in a control group or experimental group.
- If non-probability sampling (e.g., volunteer sampling) is your only choice, make sure you explain how this can cause self-selection bias and impact your findings in the discussion section of your thesis or research paper.
- Ask participants why they volunteered. Finding out why people want to participate in a study can help you evaluate to what extent their motivation may influence their responses. This, in turn, can help you assess the degree to which volunteer bias may have reduced the external validity of your research findings.
Other types of research bias
Frequently asked questions
- What are common types of selection bias?
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Common types of selection bias are:
- Sampling or ascertainment bias
- Attrition bias
- Volunteer or self-selection bias
- Survivorship bias
- Non-response bias
- Undercoverage bias
- What is the difference between self-selection bias and non-response bias?
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Self-selection bias and nonresponse bias are the opposite sides of the same issue: individuals with specific characteristics systematically (i.e., for reasons other than chance) opting in or out of a research study.
Self-selection bias occurs when the decision to participate in a study is left entirely up to individuals. This gives rise to research bias because those who volunteer to take part in research studies are usually different from those who don’t (e.g., in terms of motivation or demographics).
Nonresponse bias refers to the same phenomenon – i.e., systematic differences between those who opt in and those who opt out of a survey. However, nonresponse bias specifically refers to the fact that those unwilling or unable to take part in a study are different from those who do.
In both cases, the sample is no longer representative of the population as a whole.
- What is the difference between selection bias and self-selection bias?
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Selection bias is a broad term used to describe different situations in which the selection of study participants leads to an error (bias). As a result, the study population is not representative of the target population. Usually, selection bias is a result of an error in the study design.
Self-selection bias is a subtype of selection bias. It specifically refers to research bias caused by study participants themselves and occurs when individuals volunteer to be part of a research study.
- What is volunteer bias?
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Volunteer bias (also called self-selection bias) arises in any research study in which participants choose if they want to be part of the sample. It is a common type of research bias and leads to a sample that is not representative of the population as a whole.
Sources for this article
We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.
This Scribbr articleNikolopoulou, K. (2022, November 16). What Is Self-Selection Bias? | Definition & Example. Scribbr. Retrieved 9 December 2024, from https://www.scribbr.co.uk/bias-in-research/self-selection-bias-explained/
Oswald, L. M., Wand, G. S., Zhu, S., & Selby, V. (2012). Volunteerism and self-selection bias in human positron emission tomography neuroimaging research. Brain Imaging and Behavior, 7(2), 163–176. https://doi.org/10.1007/s11682-012-9210-3
Tripepi, G., Jager, K. J., Dekker, F. W., & Zoccali, C. (2010). Selection Bias and Information Bias in Clinical Research. Nephron Clinical Practice, 115(2), c94–c99. https://doi.org/10.1159/000312871
