Purposive sampling provides non-probability samples which receive selection based on the characteristics which are present within a specific population group and the overall study. It is a process that is sometimes referred to as selective, subjective, or judgmental sampling, but the actual structure involved remains the same.
There are several different purposive sampling types that researchers can use to collect their information.
• Heterogeneous or Maximum Variation
• Typical Case Sampling
• Deviant or Extreme
• Critical Case Sampling
• Total Population
Unlike the other sampling techniques that are useful under probability sampling, the goal of this work is to intentionally select subjects to gather information. Researchers are working with a specific goal in mind through the lens of quantitative research. The focus remains on individuals with specific characteristics in a targeted population group of interest.
Each type of sampling can be useful for situations when researchers must either target a sample quickly or for when proportionality is the primary concern. Although each type offers its own set of strengths and weaknesses to consider, they also come together to create a series of advantages and disadvantages for purposive sampling to review.
List of the Advantages of Purposive Sampling
1. You can take advantage of numerous qualitative research designs.
Researchers are able to draw upon a wide range of qualitative research designs when their focus is on purposive sampling. Achieving the goals of these designs often requires a different type of sampling strategy and technique to gather the necessary data to draw a conclusion. The various techniques that are possible through the purposive approach allow research designs to be more adaptive, allowing for specific techniques to be applied when needed to work toward the end result.
2. There is still an opportunity to create generalizations from the data.
Although you cannot extrapolate information from the targeted group to make generic claims about an entire population, the various purposive sampling techniques do provide researches with the justification to make a generalization from their sample. These efforts must be logical, analytic, or theoretical in nature to be valid. Each of the seven techniques takes a slightly different approach to this process, so it is up to the researchers involved with the project to determine how the work should proceed.
3. Purposive sampling can involve multiple phases.
Not only can purposive sampling involve multiple phases for researchers, but it can also have each phase build upon the previous one. Even though this usually means a different type of technique is necessary at the start of each phase, this process is useful because it offers a wider range of non-probability sampling opportunities from which a researcher can draw. The classic example of this advantage is that critical sample can be useful in determining the value of an investigation, while the expert sampling approach allows for an in-depth analysis of the information that is present.
4. It helps by saving time and money while collecting data.
The flexibility of purposive sampling allows researchers to save time and money while they are collecting data. It offers a process that is adaptive as circumstance change, even if it occurs in an unanticipated way. You can meet multiple needs and interests while still maintaining the foundation of a singular focal point. That is why it becomes possible to produce a final logical outcome that is representative of a specific population. You are taking a non-random approach to generate results that can then provide more information about future decisions that need to be made.
5. You can target niche demographics to obtain specific data points.
When researchers use the homogeneous purposive sampling technique to collect information, then they are selecting individuals who have a shared set of characteristics. This similarity may involve emotional reactions, physical characteristics, or even household income levels. When researchers wanted to know how Caucasian people felt about the ideas of white privilege and racism, then they asked people who were white. You could follow the same processes for people who identify with a specific gender, work for the same employer, or any other shared characteristic that is important to study.
6. It is still possible to achieve a maximum level of variation in the purposive sample.
By taking a heterogeneous approach to this research option, it is possible to select individuals from a diverse range of cases that are relevant to the issue being studied. The purpose of this design is to give researchers an opportunity to develop as much insight as they possibly can into whatever key point is under observation or examination. If you wanted to know how everyone in a community felt about a specific issue, then you would want to ask the same questions to as many different kinds of people as possible to create a strong perspective that represents the general public.
7. Purposive sampling allows researchers to look at the averages in the data.
When the typical case sampling approach is taking using this process, then researchers are usually studying an event or trend that relates to who would be considered an “average” person in that specific demographic. It is even possible at times to pull information from past research opportunities to provide relevance to the updated data. If you want to know how a change in workplace procedures affects the average employee, then it would be necessary to contact the people who fit into a defined median from your demographic studies.
8. It can glean information from the various extremes of population groups.
Purposive sampling can look at averages, but it will also help researchers to identify the extreme perspectives that are present in each population group as well. There are always outliers to consider in any project such as this, and their perspectives are just as critical at times as what the “median” person provides toward an outcome. This advantage makes it possible to have a better understanding about behavior patterns within a specific group, and it does not always need to be a negative perspective.
If researchers wanted to see why a specific group of students always achieved high grades while others did not, then they could purposely choose all of the individuals who reach the highest levels of success while ignoring everyone else.
9. You can select everyone in the population for the study with purposive sampling.
There is no better way to understand how an entire population thinks or feels than to include every perspective in the data that you collect. This purposive technique makes it possible to prove the validity of the information immediately because no one is left out from the sampling process. Although this advantage takes more time because there is a significant amount of data to collect compared to the other types that are possible, researchers save time trying to “prove” their assertions because the material is useful in its raw form.
10. The information collected in purposive sampling has a low margin of error.
When researchers approach a population group with a random survey, then the margin of error on their conclusions can be significant. Take a look at the political polls that news organizations announce regularly on their broadcasts. Most of them offer a margin of error that is between 3% to 6% – and sometimes even higher. If your results then say that individuals who say “yes” make up 48% of the population, but the people who say “no” are 52% of it, the margin of error can negate whatever result you hoped to achieve.
Researchers achieve a lower margin of error using the purposive sampling approach because the information they collect comes straight from the source. Each person has identifiable characteristics that place them into the same demographic. You’re not polling a random sample. You are working people who think or act the same way in specific situations.
11. Purposive sampling can produce results that are available in real-time.
When researchers use surveys or polls to collect data from a specific population sample, then the information they acquire is useful in real-time situations. The members of the sample group all possess an appropriate level of understanding and knowledge about the subject being evaluated, which means there is less downtime involved. You do not need to process the data to glean results because it is possible to ask targeted questions that produce the exact answers that you require in each situation.
List of the Disadvantages of Purposive Sampling
1. It provides a significant number of inferential statistical procedures that are invalid.
When you use purposive sampling for information collection, then you will discover that there is a vast array of inferential statistical procedures that are present in this structure. These statistics become invalid. They allow you to generalize from specific samples to a larger population group, making statements about the validity or accuracy of your discoveries. Because the data is more complex than what you would receive from a random sample, the only inference possibilities apply to the specific group that you are studying.
2. This process is extremely prone to researcher bias.
Purposive sampling is highly prone to researcher bias no matter what type of method is being used to collect data. The idea that a sample is created in the first place relies on the judgment of the researcher, as well as their personal interpretation of the data. When the judgments are either poorly considered or ill-conceived, then this problem becomes a significant disadvantage that can provide roadblocks in the way of a final result. When there is elicitation, accepted criteria, or a theoretical framework in place, then this issue is minimized.
3. It may be challenging to defend the representative nature of a sample.
Researchers must provide evidence that the judgment used to select the various units or individuals in the purposive sampling was appropriate for the processed used. The high levels of subjectivity cast an inevitable shadow of doubt on the results in almost every situation. Unless there is a way to defend the overall representative structures that were implemented to generate results, there will always be readers who feel unsure about the generalizations achieved, even when the theoretical, logical, or analytical structures are present.
4. The participants in purposive sampling can also manipulate the data being collected.
When people know that they’ve been selected for a research project, then it can initiate a change in their behavior. They might choose to act in a way that allows researchers to reach the conclusions that they expect to see, or the opposite issue can occur as well. Some participants may choose to lie to create an unwanted outcome because they have a bias of their own that they want to take public. Only the skill of the researchers can determine if there is validity in the data collected, which means there are times when the outcome being studied could be more unpredictable than anticipated.
5. It can be an ineffective method when applied to large population groups.
Although total population sampling is one of the purposive methods that researchers can use when collecting data, this process is at its most effective when there are a limited number of individuals or units who possess the specific traits that are being studied. Trying to initiate a random sample to serve as a foundation for theoretical supposition would be virtually impossible. You must go to the people with the specific traits that you wish to analyze for this research method to be useful. If that is not possible, then purposive sampling will not provide results at all.
6. There is no way to evaluate the reliability of the expert or authority in purposive sampling.
There are occasional exceptions to this particular disadvantage, but there is usually no way to evaluate the reliability of the authority involved or the experts who are performing the purposive sampling. That means it can be virtually impossible to determine if there is a sampling error that is present in the information that researchers present. Even when the most experienced individuals in the industry under study are presenting the information, there is room to question the interpretation of the results. That is why there are times when purposive sampling is the weakest option to choose.
7. Purposive sampling can still produce inaccurate assumptions.
When evaluating the overall sampling process, there is no randomization involved in purposive sampling because that would negate its purpose in the first place. It would not benefit researchers to speak with 40-year veterans of the workforce when they want to collect information about twenty-something entrepreneurs navigating the gig economy. There will always be a bias in this information. Because the members of the population being studied do not always have equal chances of selection, then even the logical process of sampling may generate inaccurate results.
The margin of error is smaller with this process than it would be with a randomized process, but it still exists. It may also be larger than a random sample if researchers use a large enough sample for their data collection needs.
One Final Consideration on the Advantages and Disadvantages of Purposive Sampling
Purposive sampling relies on the presence of relevant individuals within a population group to provide useful data. If researchers cannot find enough people or units that meet their criteria, then this process will become a waste of time and resources. The goal of this work is to find a range of cases that meet predetermined definitions to offer more insight into specific ideas, concerns, or issues within specific population groups.
Because the researchers are in charge of the selection process, their perspectives can influence the data they collect in numerous ways. Even when there is a conscious effort to set aside a bias, some may unconsciously manipulate the data that is available to create outcomes that support their preconceived notions.
The advantages and disadvantages of purposive sampling offer significant levels of flexibility, but they also require a higher level of evidence-based techniques to prove to outside observers that there is relevance to the information collected. That is why this process is usually reserved for situations where there is already a general consensus in the public about the definitions of certain population groups.
Crystal Ayres has served as our editor-in-chief for the last five years. She is a proud veteran, wife and mother. The goal of ConnectUs is to publish compelling content that addresses some of the biggest issues the world faces. If you would like to reach out to contact Crystal, then go here to send her a message.