What Is Purposive Sampling? | Definition & Examples

Purposive sampling, also known as judgmental sampling and selective sampling, is a non-probability method of sampling where the researcher chooses participants based on some relevant criteria. This method is most useful when the purpose of qualitative research is to develop a deep understanding rather than making wide generalisations. Targeted qualitative data collection is how this method allows the researcher to focus on very important subjects. This guide describes purposive sampling types, usage, benefits, and limitations clearly.

What Is Purposive Sampling?

With purposive sampling, you choose people on purpose because they matter for the study. Researchers use their experience and judgment to pick participants, and that’s why some call it judgmental sampling. As a non-probability purposive sampling technique, it fits well with qualitative data collection when the aim is to study a specific topic or group closely. Instead of focusing on statistics, this method values the understanding you get.

Types of Purposive Sampling

Many sampling strategies in research exist; each one serves a different goal. In purposive sampling, researchers might try to include a range of different people, focus on experts, or single out particular cases. Making these choices helps reach the exact population the research needs. Below, you will see the main types explained:

Maximum Variation Sampling

Using maximum variation sampling, researchers involve people from different backgrounds to see patterns that cut across cases. This approach is part of qualitative research’s effort to use sampling strategies in research that show diversity. It works for building a picture of a group with different experiences.

Homogeneous Sampling

Homogeneous sampling is useful when a researcher wants to study a smaller group within a larger one that shares the same features. This method allows qualitative data collection to be more focused, and in judgmental sampling, it finds those with similar traits. Researchers go for this option when sameness among participants is important.

Typical Case Sampling

In typical case sampling, cases are chosen that are normal or common for the group being studied. It is helpful for mixed methods research where both types—qualitative and quantitative benefit from average information. This method represents a traditional purposive sampling type.

Critical Case Sampling

Critical case sampling means selecting examples that have special importance or meaning for the research. This sampling strategy in research is popular for qualitative research because it highlights data that can be transferred to other cases. With this approach, collecting data becomes more solid and reliable.

Expert Sampling

Expert sampling focuses on picking people with deep knowledge or specific skills. This variant of judgemental sampling is key in mixed methods research as it combines expert views with bigger data sources. Choosing experts like this ensures the quality of qualitative data collection stays high.

Snowball Sampling (As a Variant)

Although it is a bit different, snowball sampling starts with purposive sampling and then grows the sample through referrals. It is very helpful when researchers need to collect qualitative data from people who are hard to find. This complement to data collection methods in qualitative research extends the reach for participants.

Advantages of Purposive Sampling

Purposive sampling lets researchers use time and resources wisely in qualitative research. Gaining deep understanding from a carefully chosen target population in research is much easier with this technique. Almost every data collection method in qualitative research works well alongside qualitative data collection methods purposive sampling, especially in exploratory or mixed methods research settings. With this approach, researchers stay in command, which lifts the accuracy of their results.

Limitations of Purposive Sampling

Since purposive sampling is one type of non probability sampling method, it carries the danger of bias and not being generalizable. If the researcher picks the wrong people, the credibility of qualitative data collection can go down. When judgmental sampling is used too much, important voices might get left out, so the sampling strategies in research must be picked with care.

Real-World Examples of Purposive Sampling

In healthcare research, sometimes only specialists get interviewed, showing classic expert sampling done through judgmental sampling. For education studies, researching the best schools requires getting data from a specific target population in research. These cases make it clear that purposive sampling adds depth to qualitative data collection methods.

Purposive Sampling vs. Other Sampling Techniques

While random or probabilistic sampling techniques try to be representative, purposive sampling takes a different path. It is distinct from convenience sampling and even shares some points with snowball sampling, but the overlaps don’t make them equal. The strongest point of purposive sampling lies in qualitative research, where tailored sampling strategies in research boost the power of data collection methods in qualitative research.

When to Avoid Purposive Sampling?

If research needs results to be statistically generalizable and truly objective, purposive sampling is not the right fit. For studies requiring randomisation, choosing non-probability purposive sampling would not meet the requirements of some mixed methods research. At such times, it’s smarter to look for other sampling strategies in research.

Conclusion

Purposive sampling stands out as a powerful option among sampling strategies in research, making focused and deep studies possible. It holds a key role in qualitative research and is being used more in mixed methods research, too. At Assignment In Need, we recognise that when purposive sampling is matched with good data collection methods in qualitative research—especially judgmental sampling—it brings out detailed and valuable insights.