Purposive sampling is a non-randomized sampling technique that selects sampling units based on certain criteria. Purposive research sampling is a type of non-probability approach in which the researcher chooses a sample (person, cases, or events) based on their assessment that it would fit the study’s objectives. As a result, purposive sampling is an intentional and strategic selection procedure that uses samples to explore their specific characteristics. In this article, we will look at the key features, applications, and limitations of the purposive sampling technique.
What is a purposive sampling?
Purposive sampling, also known as judgmental or expert sampling, involves intentional selection of participants based on the researcher’s expertise. Participants are chosen deliberately, not randomly, to align with specific study objectives. This method is suitable for small populations with a clear research purpose, allowing the researcher to target individuals with specific attributes relevant to the study. For instance, in exploring vegans’ reactions to a new mock meat product, participants are purposefully selected for their vegan lifestyle. Purposive sampling is commonly used in qualitative research, providing in-depth insights from individuals who offer valuable perspectives on the research questions. In summary, the purposive sampling technique tailors participant selection to the research goals, promoting a nuanced and contextually rich understanding of the studied phenomena.
When to use purposive sampling?
Now that you know the definition of purposive sampling, let’s delve into when this should be used. Purposive sampling is ideal for small samples requiring a deep understanding of specific characteristics related to the research question. In purposive sampling, the final sample is typically a subset of the population with similar features. The idea behind purposive sampling is to select cases, individuals, or communities that serve as the dataset from which meaningful information pertaining to the research question can be derived. As a result, it is critical that you have a thorough understanding of the study background before using the purposive sampling approach to collect data for your research topic.
Before you begin your research, you must first define your purpose or research question. Then, you will select only those units or individuals who are best equipped to answer your question. Purposive sampling is suitable in scenarios where researchers aim to study specific characteristics, such as examining the mitigating strategies employed by young climate change advocates. In this case, purposive sampling is employed to specifically select young individuals engaged in climate change advocacy. Another scenario for purposive sampling is when researchers need to choose participants with expertise or knowledge, opting for individuals considered experts in a certain field or possessing specific skills relevant to the research topic.
Purposive sampling methods and examples
Purposive sampling approaches entail selecting participants based on specified criteria or features related to the research subject. There are various sorts of purposive sampling methods that can be utilized depending on the type of research and research objectives:
- Homogeneous sampling
- Typical case sampling
- Maximum variation (or heterogeneous) sampling
- Extreme (or deviant) case sampling
- Critical case sampling
- Expert sampling
Homogeneous sampling
Homogeneous sampling, a purposive method, minimizes variation in the selected sample for a simpler and more robust analysis. It enables an in-depth exploration of a specific subgroup, with individuals sharing similar attributes like demography, perspectives, occupations, or cultures. The focus in homogenous sampling is on commonalities among samples and their relevance to the research topic.
Example:
In a study aimed at comprehending the unique experiences of long-term employees in a high-demand IT industry, researchers may employ homogeneous sampling. This involves selecting participants from the same corporate setting, focusing on criteria such as (i) full-time employment, (ii) a minimum of five years in the IT industry, and (iii) high levels of work-related stress. Analyzing this targeted group enables an in-depth exploration of work-related stress, coping mechanisms, and the potential impacts of mitigating measures.
Typical case sampling
Typical case sampling is a type of purposive sampling in qualitative research used to choose participants who exemplify typical or average instances of the phenomenon being studied. These selected individuals exhibit behavior and characteristics similar to other participants in the sample. The aim of typical case sampling is to study typical or normal behavior of the selected individuals to gain comprehensive understanding of the common features linked with the phenomenon. This allows the researcher to identify patterns, themes, or regularities within a certain context.
Example:
In a study focused on exploring the experiences of immigrant college students adapting to a new country and university life, the researcher can employ typical case sampling. The students’ experiences can be collected via surveys or interviews to create a dataset of typical immigrant college student experience. Analyzing this dataset provides deeper insights into typical challenges faced by immigrant college students, informing potential adjustments to university policies to create a safer and more comfortable environment for them. It’s important to note that typical case sampling is employed to understand a phenomenon rather than to draw generalizations.
Maximum variation (or heterogeneous) sampling
Maximum variation, also known as heterogeneous sampling, is employed to choose participants with a diverse range of characteristics related to the research question. To put it simply, in this type of purposive sampling, the researcher intentionally chooses participants who display different perspectives to cover a broad range of perspectives. The objective is to capture diverse experiences and situations, facilitating the identification of common patterns and differences within the phenomenon under investigation.
Example:
In examining the influence of career counseling programs on college students’ career development, adopting maximum variation sampling involves intentionally selecting candidates from various academic streams and different colleges. To enhance diversity, colleges from different locations within the city or state can be chosen. This intentional choice aims to include college students with broad variations, considering different areas and demographics. This sampling approach enables the researcher to attain a comprehensive understanding of the complex and multifaceted topic. Analyzing the collected dataset allows for the identification of patterns, trends, and unique characteristics emerging across the diverse group of participants.
Extreme (or deviant) case sampling
Extreme case sampling is performed when there is a need to highlight unusual cases or outliers in the population. The objective of extreme case sampling is to study instances that significantly deviate from the norm, whether exceptionally successful, unsuccessful, unique, or extreme in other aspects relevant to the research question. Also known as deviant case sampling, this purposive sampling technique is typically utilized to gain insights into the boundaries or limits of a phenomenon and understand the factors influencing such extremes.
Example:
If a researcher is keen on investigating the impact of educational interventions on academic performance in a school district, an application of extreme case sampling would involve selecting two schools that represent polar extremes in terms of academic achievement. By choosing schools with either exceptionally high or low academic outcomes, the researcher gains insights into the factors contributing to these extremes within the district. This understanding may unveil unique practices, policies, or contextual factors influencing the variations in academic performance.
Critical case sampling
Critical case sampling, a qualitative method, is employed when the researcher deliberately selects samples crucial for the phenomenon under investigation. The goal is to focus on information-rich cases that offer valuable insights into the crucial aspects of the phenomenon. Analyzing critical cases allows the researcher to extrapolate findings to similar cases, making critical case sampling an initial step in research to determine if further in-depth analysis is warranted.
Example:
When studying the effectiveness of a community-based health intervention program aimed at reducing the prevalence of a specific health condition, a researcher may opt for a critical sampling approach. This involves selecting two types of communities: one where the health program has been successfully implemented and another where the implementation has failed. This sample selection enables the identification of factors contributing to success, as well as barriers and contextual issues hindering implementation. The insights gained can inform future strategies for the health intervention program.
Expert sampling
Expert sampling is used when the research requires individuals with specific expertise on the topic. Participants are chosen based on demonstrated skills or relevance to the research focus. This method is common in exploratory research, especially when observational evidence is limited.
Example:
Imagine a researcher aiming to investigate the influence of emerging technologies on the future of artificial intelligence in healthcare. To gather insights, expert sampling can be employed to identify individuals with expertise in artificial intelligence, healthcare, and technology. The criteria for selection may include advanced degrees, extensive experience in research or work, and relevant publications in these fields.
Step-by-step guide to purposive sampling with examples
Purposive sampling becomes crucial in qualitative research aimed at in-depth understanding of a specific phenomenon. Here is a step-by-step guide, including purposive sampling examples, for planning such a study.
- Define your research question: Begin the purposive sampling process by clearly defining the specific research question you aim to address. Identify the essential aspects and characteristics you intend to explore in your study, setting the foundation for your research design and methodology. For instance, consider a research problem focused on examining the impact of meditation and sound therapy on enhancing the mental well-being of middle-aged individuals (30-45 years) experiencing free-floating anxiety.
- Identify the purpose of sampling: Proceed to identify the goal of your sampling, outlining what you aim to accomplish with your study. Whether it is attaining a comprehensive understanding of a specific subgroup, capturing diverse perspectives, or exploring all relevant characteristics within the population.
- Decide your target population: Specify the population from which your sample will be drawn to gather meaningful conclusions. For instance, in the previously mentioned example focusing on meditation and sound therapy intervention for middle-aged individuals, the target population comprises middle-aged individuals diagnosed with generalized anxiety.
- Determine the criteria for selection: Identify the characteristics, traits, or conditions most pertinent to your research question for the deliberate selection of individuals meeting the criteria. For instance, if your interest lies in studying those individuals who exhibited exceptional responses to meditation and sound therapy, and you seek to understand the reasons behind this, you can choose extreme case sampling, concentrating solely on the best-performing cases.
- Data collection using a well-suited method: Select an appropriate data collection method aligned with your research goal using a purposive sampling method. For example, in the previously mentioned example focusing on meditation and sound therapy intervention, data can be gathered through various means such as interviews, surveys, or observations, involving both the mental health professional conducting the intervention and the participants undergoing the treatment.
- Result analysis and interpretation: Prior to delving into result analysis, acknowledge the biases that may have emerged due to the intrinsic nature of purposive sampling, which can introduce potential biases in the methodology. It’s essential to refrain from generalizing beyond the sampled population.
Advantages and disadvantages of purposive sampling
Purposive sampling finds extensive application in qualitative research; nonetheless, it’s crucial to consider both the advantages and disadvantages associated with purposive sampling techniques.
Advantages of purposive sampling
Purposive sampling has several advantages, some of them are listed here:
- With purposive sampling you can make generalization from the sample being studied compared to a random sample where not all participants might have similar characteristics. However, it is not possible to make statistical inferences from the sample to the population.
- Another significant benefit is the range of purposive sampling methods available for researchers to choose from based on their research requirements and objectives. Given that qualitative research is often conducted in distinct phases, employing different purposive methods for each phase enables researchers to build upon the findings of the preceding stage.
- Purposive sampling is economical and can produce reliable results in real-time.
- Purposive sampling has less chance of sampling error.
Disadvantages of purposive sampling
Despite the advantages of purposive sampling, there are some drawbacks too.
- Purposive sampling is prone to research bias as the samples are not collected randomly and are based entirely upon the judgement of the researcher leading to the risk of observer bias.
- Generalizations beyond the sampled population is not possible. Hence, no statistical inference can be made.
- Participants’ awareness of their involvement in the research can introduce bias into the study.
Purposive sampling is utilized in situations with smaller population sizes and relies on the accessibility of relevant sample units. Despite this constraint, the intentional selection of participants results in an information-rich sample set. This richness facilitates the extraction of meaningful and relevant insights, potentially guiding future research strategies and interventions.
Frequently asked questions
- What is the difference between purposive sampling and convenience sampling?
Purposive sampling and convenience sampling are both employed in qualitative research, but they differ significantly. Convenience sampling involves data collection based on the researcher’s convenience without necessarily distinguishing participant characteristics. In contrast, purposive sampling focuses specifically on selecting participants with characteristics relevant to the research question.
- What is the difference between purposive sampling and random sampling?
Purposive sampling involves intentional selection based on specific criteria whereas in random sampling participants are selected based on chance selection, where everyone has an equal chance of being selected. Purposive sampling also allows for targeted inclusion, while random sampling aims for unbiased representation.
- What is the sample size for purposive sampling?
The sample size for purposive sampling will vary depending upon the research question, specific goals of the study, the nature of the research question, and the in-depth knowledge required. Generally, researchers select participants until they reach a point of saturation, where additional participants do not contribute significantly new information or insights. However, a sample size of 30 individuals is usually deemed as sufficient for qualitative research, while in some cases larger sample sizes are needed.
- What is the purpose of sampling in research?
Sampling in research aims to efficiently select a subset of a population for study, making data collection feasible and allowing researchers to draw meaningful conclusions and generalize findings to the larger population.
- What are the principles of purposive sampling?
Purposive sampling involves intentionally selecting participants based on a purpose, i.e., clear criteria, aligned with research goals, to maximize information richness and gain in-depth insights.
- How is purposive sampling conducted?
Purposive sampling is conducted by defining research objectives, establishing criteria, selecting participants intentionally, recruiting participants, collecting and analyzing data, and drawing conclusions in alignment with the study’s objectives.
- What type of research uses purposive sampling?
Qualitative research, such as exploratory research, is usually based on purposive sampling.
- What is an example of purposive sampling?
An example of purposive sampling is a research study that examines the experiences of female entrepreneurs in the biotechnology industry. Based on the research objectives, the researcher can select female entrepreneurs in the biotechnology industry adding further filters such as age, professional experience, geography, as needed to answer the research question.
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