Purposeful sampling is a non-random sampling technique that utilizes a specific criteria or purpose to select particular sample. The researcher may use one or more than one strategies or criteria to select the sample. The aim is to collect in depth information from the right respondents.
Principles of purposeful sampling
The basic principle of purposeful sampling is that information is available and the researcher needs to identify what segment of the population can provide that information. The researcher selects that segment and collects information from them by using any tool like questionnaire, interviews or other survey related tools. This enables the researcher to gather right informants and rich information. However it is important that in doing so the researcher provides the rationale of the selection of a particular sample.
Qualitative research relies on non-random sampling techniques because these techniques provide deep information about the subject. Obviously, this is not the case with quantitative research where the aim is to get information that is more generalizable and hence has a breadth. Therefore, purposeful sampling is more commonly used in qualitative studies. However, the researcher needs to be aware that there is a criteria that defines the selection of a particular sample. When a specific criteria is followed to select a sample it is called as criterion purposeful sampling. This kind of sampling technique is useful in adding depth in even a quantitative research. The criteria of sample selection should be in accordance with the topic and aims of the research.
Whether purposeful sampling is used in qualitative research or quantitative research the aim should be to have a sample that adds to the validity of the research. It should improve the efficiency and credibility of research. Also it should have a consistency with the aims and purposes of the research. Only in this way purposeful sampling can become worthwhile for the research.
It is also important that a particular sample that the researcher selects from the target population based on purposeful sampling should have variation. But it is often times difficult to understand the type of variation in the population especially when the population is large. Once the researcher selects the sample and interviews them it is easier to establish and understand that variation. Therefore, sometimes the researchers select sample twice because in this way they can make sure that sample is representative of the variation in the population. A multistage sampling technique can help in achieving this goal. Although multistage sampling is not always possible because it is time consuming and costly.
Benefits of purposeful sampling
- The basic benefit of this sampling technique is that rich information is possible to collect on even a low budget.
- It is easier to get in-depth information since the researcher identifies the right audience and selects them.
- On a small budget the researcher cannot employ systematic random sampling and if used properly this sampling method can substitute systematic sampling.
- Since it is non-random sampling and the researcher selects sample according to his own choice the chances of bias are there. The researcher should know how he can limit or reduce bias in the selection of sample.
- A non-random selection also makes it less reliable and replicable than a random selection. The researcher can provide evidence in the study for the need to use this method.
- Some respondents may not be willing to share information or may not be open to it. The researcher should know how to deal with this problem.
To better understand the purpose of purposeful sampling one should read this definition by Patton (2002, p. 230), who has defined this method in the best manner.
“The logic and power of purposeful sampling lie in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling. Studying information-rich cases yields insights and in-depth understanding rather than empirical generalizations.”Patton MQ. Qualitative Evaluation and Research Methods (2nd Ed.).
All the shortcomings that many researcher claim about purposeful sampling are targeted towards its lack of generalization. As the above definition states purposeful sampling is aimed to obtain deep information. But their are many ways in which you can conduct purposeful sampling: one way is to do intensity sampling; another way is to do variation sampling. The choice of sampling technique in this sampling depends on the aims f the research.
a. Intensive purposeful sampling
In this technique of purposeful sampling the researcher selects samples that can provide deep insight on the topic. Although this kind of purposeful sampling ignores variation in the data but it is sometimes very useful. Especially when the aim is to dig deep than to study breadth of information. Also this is sometimes a good starting point and yields insight on further sampling and adding more breadth or variation to the sample.
b. Variation sampling
Variation sampling as the name suggests considers studying a wider variety of sample that does not exclude any segment of society. It provides a broad range of data but it is time consuming and may be costly. The researcher first determines the extent an type of variation in the population. Then he selects sample that represent that variation purposefully. It is important however that it is possible for the researcher to identify variation in the population.