What is judgmental sampling and what are its merits?

Judgmental sampling, sometimes called purposive, selective, or subjective sampling, is a non-probability method where researchers choose participants on purpose because they have qualities that matter to the study.

Unlike random sampling, which tries to cover a wide mix of people to reduce bias, this approach focuses only on the groups or traits that are most useful for the research. It is commonly used in healthcare, social sciences, marketing, and opinion polling.

There are different types of purposive sampling. Typical case sampling looks at participants who represent the “average”. Extreme case sampling focuses on unusual or outlier cases, while critical case sampling studies one key person or event for deeper insight.

Heterogeneous sampling includes various participants to find shared themes, whereas homogeneous sampling looks at people with similar traits to understand specific group behaviours. Finally, theoretical sampling develops as research goes on, helping to identify patterns and connections between different groups.

Its merits lie in efficiency, focus, and its ability to capture valuable insights from specific groups in qualitative research. However, its limitations include the risk of bias and generating a non-representative sample, which reduces the ability to generalise results to a larger population.

How does judgmental sampling work in practice?

As a non-probability method, researchers hand-pick participants they believe will provide the most useful or representative information for the study. It relies on the researcher’s knowledge and expertise to choose people or groups that best fit the research goals.

In practice, this means participants are chosen deliberately because of certain qualities or characteristics they possess. The researcher decides who is most suitable for the study to ensure the sample directly supports the purpose of the research.

Judgment sampling has existed since the early 20th century, especially in qualitative research. Researchers began using it to collect more targeted insights and gain a deeper understanding of specific issues. Today, it is widely used in fields like social sciences, market research, and healthcare, where focused and detailed information is essential.

How do researchers define research goals before applying judgmental sampling?

Researchers begin by clearly identifying research objectives. Defining goals ensures that the selection process aligns with what the research study intends to measure.

For instance, if the objective is to understand the effect of socioeconomic status on education, only participants with relevant backgrounds may be selected based on this specific criterion.

The results remain directly linked to the study’s purpose by focusing on defined objectives. Without this clarity, gathering data could lead to inconsistent findings and undermine the usefulness of the sampling method.

What key characteristics are identified in participants?

In judgmental sampling, a researcher looks for certain participant characteristics that reflect the target population. These may include:

• Socioeconomic status (income, education, or occupation)
• Membership of specific groups (such as healthcare professionals, students, or policy-makers)
• Possession of relevant expertise useful to the research study

By applying these criteria, a relatively small sample can be chosen that still provides valuable insights. Researchers pick participants who have specific qualities that fit the study. It helps focus on groups likely to give useful insights, but the drawback is that the sample might not fully represent the wider population.

On the other hand, convenience sampling (also called availability sampling) involves choosing people simply because they are easy to reach or available at the time. This method is quick, low-cost, and practical, especially when resources are tight. However, it also risks bias and may not accurately reflect the population.

How does a researcher select participants based on expertise or traits?

A researcher selects participants based on their knowledge or specific traits that serve the research objectives. This might include choosing doctors for a medical trial (expert sampling), community leaders for social studies, or consumer panels in focus groups.

This method is cost-effective and less time-consuming compared to other sampling techniques like random or snowball sampling. By deliberately targeting participants with relevant expertise, researchers can collect more meaningful data for decision-making, even when working with a small number of individuals.

When should judgmental sampling be used in research?

This method is not always suitable, but it proves especially useful in certain situations. Researchers often use judgmental sampling when resources are limited, in-depth insights are needed, or specific expertise is essential.

Why is judgmental sampling suited for limited resources?

Judgmental sampling is suited for limited resources because it focuses on a small sample rather than a larger population. This makes the sampling process cost-effective and less time-consuming, helping researchers achieve their research objectives without overextending budgets.

Smaller sample-based studies may be conducted to evaluate specific policy interventions. By narrowing the selection process to participants with certain characteristics, researchers can collect useful data without the expenses linked to probability sampling techniques.

How is judgmental sampling useful in qualitative research?

Judgmental sampling is highly useful in qualitative research because it targets specific groups or individuals with relevant expertise. Qualitative research aims not at statistical generalisation but at obtaining valuable insights into behaviours, experiences, and attitudes.

Focus groups of parents in Singapore could help education researchers evaluate new teaching policies. Unlike haphazard or convenience sampling, judgemental sampling ensures that the results align with the research objectives, even with a relatively small sample.

When do researchers rely on expert-driven studies?

Researchers rely on expert-driven studies when relevant expertise is required to address the research objectives. This is often referred to as authoritative sampling or expert sampling, where a researcher selects participants based on their knowledge of the subject.

Singapore’s Urban Redevelopment Authority may consult urban planners with decades of experience in policy evaluation. Here, the method does not aim for a representative sample but to capture high-value insights from individuals with relevant expertise.

Why is judgmental sampling applied to information-rich cases?

Judgmental sampling is applied to information-rich cases to extract valuable insights that cannot be obtained from random selection. Deviant case sampling, which focuses on unusual or extreme cases, is often used to achieve this.

Researchers studying high-performing schools in Singapore may choose outliers that significantly exceed national averages. While such a non-probability sampling method does not represent the larger population, it helps uncover patterns or practices that may be applied in different locations or specific subgroups.

What are examples of judgmental sampling in real-world studies?

Judgmental sampling is widely applied across industries. From healthcare to education and even market research in Singapore, it helps researchers concentrate on participants who can provide the most meaningful data.

Imagine a study to discover why people choose ethical hacking as a career. Since ethical hacking is a specialised skill, the researchers must carefully select participants who understand the field. In this case, judgmental sampling helps filter out irrelevant participants, ensuring the study focuses only on people with the right background.

Another example is when researchers want to study religious beliefs among different tribes. For instance, the Balinese practise syncretism, a blend of Hinduism and Buddhism. Because religion is such a sensitive subject, researchers would use judgmental sampling to select participants with the right knowledge and understanding.

This approach ensures more accurate results than random sampling, which could otherwise include people without the necessary insight.

How is judgmental sampling used in healthcare research?

Judgmental sampling is used in healthcare research to target specific groups of patients or professionals. For example, a researcher selects participants based on specific criteria such as age, medical history, or socioeconomic status.

The Ministry of Health frequently publishes reports informed by sample-based studies focusing on chronic illnesses. Unlike random selection, this approach allows researchers to collect data directly relevant to healthcare challenges, offering valuable insights while using a small number of cases.

What role does judgmental sampling play in education research?

Judgmental sampling is critical in education research, focusing on specific groups of students, teachers, or institutions. Researchers may use focus groups with educators to evaluate curriculum reforms or select students from different locations with certain characteristics, like learning difficulties.

The Ministry of Education uses targeted sampling methods to design policies and improve academic outcomes. Although the non-representative sample cannot be generalised to the larger population, it helps shape effective strategies.

How is judgmental sampling applied in market research in Singapore?

Judgmental sampling is applied in market research to target specific subgroups of consumers. Businesses often select participants who best represent their target population, such as working professionals, retirees, or young adults in urban areas.

Surveys may focus on residents in Singapore’s central districts to better understand spending behaviours. The Department of Statistics Singapore uses similar sampling methods to conduct economic surveys, proving how judgment sampling helps researchers gather data efficiently while maintaining focus on specific criteria.

What are the main advantages of judgmental sampling?

Like any approach, judgmental sampling has its strengths. Its ability to target relevant individuals, save resources, and focus on knowledge-rich cases makes it attractive for many researchers.

Why does judgmental sampling target specific knowledge effectively?

Judgmental sampling targets specific knowledge effectively because participants are selected based on relevant expertise or certain characteristics. This ensures the results align closely with the research objectives, making the sampling process purposeful.

In focus groups of medical professionals, the researcher’s knowledge allows them to select participants who provide valuable insights into healthcare trends.

Compared with other sampling techniques, such as convenience or haphazard sampling, judgemental sampling captures more reliable and meaningful information for the study.

How does judgmental sampling save time and resources?

Judgmental sampling saves time and resources by focusing on a relatively small sample instead of a larger population. The selection process is faster, less time-consuming, and more cost-effective.

Businesses in Singapore often rely on sample-based consumer studies using judgment sampling instead of a full random sample survey.

This allows them to collect data quickly while still addressing the research objectives. By targeting specific groups, researchers reduce the cost and effort required to reach broader populations.

What are the disadvantages and risks of judgmental sampling?

While judgmental sampling can be highly effective, it is not without drawbacks. Concerns about bias, lack of representativeness, and limited generalisability mean that researchers must exercise caution when using this method.

Why does judgmental sampling involve potential bias?

Judgmental sampling involves potential bias because the researcher’s subjective judgment determines the selection of participants. Unlike probability sampling techniques, where each member of the population has an equal chance of being included, this method relies heavily on the researcher’s knowledge and interpretation.

Such bias may lead to skewed results, particularly if the criteria for choosing participants are unclear or influenced by assumptions. This is why researchers must remain cautious, applying transparent guidelines to reduce the risks of bias during data collection.

How does a non-representative sample limit generalisability?

A non-representative sample limits generalisability because findings cannot be confidently applied to a larger population. Since sampling is a non-probability approach, judgment sampling often produces a non-representative sample.

Studying only high-income consumers in Singapore would exclude the perspectives of other specific subgroups. While the results obtained may still provide valuable insights, they cannot be generalised beyond the chosen sample, unlike outcomes from probability sampling techniques that use random selection.

FAQs

To clear up any confusion, here are answers to some of the most common questions about judgmental sampling. These provide quick, straightforward insights into how the method works and what researchers should consider.

1. Is judgmental sampling the same as purposive sampling?

Yes, judgmental sampling is another term for purposive sampling. Both describe a non-probability sampling method where a researcher selects participants based on specific criteria, relevant expertise, or the researcher’s judgment, rather than using random selection.

2. What are the main advantages and disadvantages of judgmental sampling?

The advantages include being cost-effective, less time-consuming, and useful for qualitative research targeting specific groups. The disadvantages include the risk of bias and generating a non-representative sample, which reduces the ability to apply findings to a larger population.

3. Can judgmental sampling results be generalised to a larger population?

Generally, no. Judgmental sampling produces a sample based on the researcher’s subjective judgment, so it lacks the fairness of random selection in probability sampling techniques. While the results may provide valuable insights for a research study, they cannot usually be generalised to a larger population.

Conclusion

So, what is judgmental sampling? This non-probability sampling technique relies on the researcher's judgment to select participants with specific characteristics or relevant expertise. While it offers several advantages, such as being cost-effective and suited to qualitative research, it also carries risks of bias and producing a non-representative sample.

Milieu is one of the leading online survey software providers and market research agencies in Singapore, specialising in turning complex methods like judgmental sampling into practical insights that businesses can act on. By combining smart research techniques with powerful survey tools, Milieu helps organisations capture the right voices and make confident, data-driven decisions in today’s fast-changing world.

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