A key part of any research project is getting workable data from the general population. Without this, your research is shallow, one-sided and lacking in any real proof. It is for this reason that some form of sampling is generally carried out, and one of the most popular sampling methods is a process known as purposive sampling.
Part 1: What Is Purposive Sampling?
So, what is purposive sampling and why would you use it? Simply put, purposive sampling is when a researcher chooses specific people within the population to use for a particular study or research project. Unlike random studies, which deliberately include a diverse cross section of ages, backgrounds and cultures, the idea behind purposive sampling is to concentrate on people with particular characteristics who will better be able to assist with the relevant research.
For example, if you are researching workplace packages that include dental benefits, then, logically, you would not include people who are unemployed or who have not been offered a benefits package by their place of work; they would be unable to relate anything relevant to your study. Rather, you would focus on people who were employed and who had dental included in their workplace benefits package.
Part 2: Advantages and Disadvantages of Purposive Sampling
1. Advantages of Purposive Sampling
- 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.
2. Disadvantages of Purposive Sampling
- 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.
- Difficult to defend. When a researcher publishes their findings, they need to be able to successfully defend their proposal from critics. Because of the non-probability nature of purposive sampling, it can be more difficult for a researcher to mount a solid defense. A critic may argue that if different selections had been made during the purposive sampling, a different result could have been achieved.
Part 3: Commonly Used Purposive Sampling Methods
1. Maximum Variation Sampling
The idea behind MVS is to look at a subject from all available angles, thereby achieving a greater understanding. Also known as “Heterogeneous Sampling”, it involves selecting candidates across a broad spectrum relating to the topic of study. For example, if you were researching an education program, you would include students who hated the program, students classed as “typical” and students who excelled. This type of sampling is useful when you can’t take a random sample, for instance, if the sample pool is too small.
2. Homogeneous Sampling
This form of sampling, unlike MVS, focuses on candidates who share similar traits or specific characteristics. For example, participants in Homogenous Sampling would be similar in terms of ages, cultures, jobs or life experiences. The idea is to focus on this precise similarity and how it relates to the topic being researched. For example, if you were researching long-term side effects of working with asbestos, for a Homogenous Sampling, you would only select people who had worked with asbestos for 20 years or longer.
3. Typical Case Sampling
TCS is useful when you are dealing with large programs, it helps set the bar of what is standard or “typical”. Candidates are generally chosen based on their likelihood of behaving like everyone else. For example, if you were researching the reactions of 9th grade students to a job placement program, you would select classes from similar socio-economic regions, as opposed to selecting a class from an a poorer inner city school, another from a mid-west farming community, and another from an affluent private school.
4. Extreme/Deviant Case Sampling
The polar opposite of Typical Case Sampling, Extreme (or Deviant) Case Sampling is designed to focus on individuals that are unusual or atypical. This form of sampling is more often used when researchers are developing “best in practise” guidelines or are looking into “what not to do”. An example would be a study into heart surgery patients who recovered significantly faster or slower than average. Researchers would be looking for variations in these cases to explain why their recoveries were atypical.
5. Critical Case Sampling
Extremely popular in the initial stages of research to determine whether or not a more in depth study is warranted, or where funds are limited, Critical Case Sampling is a method where a select number of important or “critical” cases are selected and then examined. The criterion for deciding whether or not an example is “critical” is generally decided using the following statements: “If it happens there, will it happen anywhere?” or “if that group is having problems, then can we be sure all the groups are having problems?”
6. Total Population Sampling
On occasion, it may be that leaving out certain cases from your sampling would be as if you had an incomplete puzzle – with obvious pieces missing. In this instance, the best sampling method to use is Total Population Sampling. TPS is a technique where the entire population that meet your criteria (e.g. specific skill set, experience, etc.) are included in the research being conducted. Total Population Sampling is more commonly used where the number of cases being investigated is relatively small.
7. Expert Sampling
As indicated by the name, Expert Sampling calls for experts in a particular field to be the subjects of your purposive sampling. This sort of sampling is useful when your research is expected to take a long time before it provides conclusive results or where there is currently a lack of observational evidence. Expert sampling is a positive tool to use when investigating new areas of research, to garner whether or not further study would be worth the effort.
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