Purposive sampling represents a group of different non-probability sampling techniques. Also known as judgmental, selective or subjective sampling, purposive sampling relies on the judgement of the researcher when it comes to selecting the units (e.g., people, cases/organisations, events, pieces of data) that are to be studied. Purposive sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest.
- Wide range of techniques. Since there are several different types of purposive sampling (e.g. homogenous sampling, expert sampling, critical case sampling, etc.), one of the key benefits of this sampling method is the ability to gather large amounts of information by using a range of different techniques. This variety will, in turn, give you a better cross-section of information.
- Stage building blocks. Qualitative research usually involves a number of different phases, with each phase building progressively onwards from the original. This being the case, purposive sampling is useful to a researcher because they can use the variety of methods available to build and increase their research data. For example, you could start with critical case sampling, and then using the information gathered, progress to expert sampling in stage two.
- Researcher bias. The main disadvantage of purposive sampling is the high probability of researcher bias, as each sample is based entirely on the judgment of the researcher in question, who generally is trying to prove a specific point. For this reason, researchers need to strive to make decisions based on accepted criteria, not on what will best support their theory.
- The subjectivity and non-probability based nature of unit selection (i.e., selecting people, cases/organisations, etc.) in purposive sampling means that it can be difficult to defend the representativeness of the sample. In other words, it can be difficult to convince the reader that the judgement you used to select units to study was appropriate. For this reason, it can also be difficult to convince the reader that research using purposive sampling achieved theoretical/analytic/logical generalisation. After all, if different units had been selected, would the results and any generalisations have been the same?