Convenience sampling is a non-probability technique where units are included in the sample because they are easily accessible to the researcher.
This accessibility can be based on factors like proximity, availability, or willingness to participate. Also known as accidental sampling, convenience sampling is a form of non-random sampling.
Examples of Convenience Sampling
Imagine you’re studying public perceptions of Seattle. You’ve decided on a sample size of 100 people for your research. To gather data, you station yourself at a subway stop and approach individuals, asking if they’d like to participate until you reach your target sample.
Note: It’s crucial not to mistake random selection for stopping people randomly. In random sampling, each unit has an equal chance of being chosen. However, in convenience sampling, stopping people at random means not everyone has an equal chance of being included; for instance, those who didn’t pass through that subway stop during your data collection time.
Methods of Convenience Sampling in Research
- Online recruitment through advertisements or social media posts.
- In-person recruitment at events, on the street, or at relevant locations.
- Using crowdsourcing websites like MicroWorkers.
- Sampling from pre-existing groups such as organizations or college students.
When to use Convenience Sampling?
- Convenience sampling is commonly used in qualitative and medical research studies.
- In medical research, it involves selecting available clinical cases or participants from specific locations, like hospitals or medical records databases.
- Qualitative research in the social sciences and education often uses convenience sampling with pre-existing groups, like students.
- Convenience sampling is suitable for understanding attitudes, running survey pilots, and generating hypotheses.
- However, it can introduce biases such as selection bias and sampling bias.
Example: Convenience sampling conducted online
You’re doing some research on how parents use a well-known parenting forum website. You want to know what kind of information parents are looking for online, as well as if they are likely to “lurk” or join in discussions.
There isn’t a membership list to use as a sample frame because it’s an online community. This is a situation where convenience sampling works well. You choose to select the 100 people as a convenience sample.
The administrators approve the pop-up advertisement you make inviting users to finish your online survey to be displayed on the website. The advertisement mentions a prize draw that encourages users to take part.
Example: Convenience sampling based on location
Let’s say you are investigating the reasons behind visitors to your county’s most well-liked recreational area, Green Valley State Park. You approach people at random in a parking lot to get information by asking them if they would be interested in taking part in an anonymous five-minute survey on their preferred recreational activities.
Additionally, you design flyers with a shortened URL link and a scannable QR code to increase the number of responses. You set them up at the lake’s welcome center and other locations.
Crowdsourced Convenience Sampling Example
Suppose you’re researching attitudes toward blood pressure across different cultural backgrounds, specifically focusing on collectivistic and individualistic cultures. Since you lack an extensive international network, you opt for a crowdsourcing platform like Amazon Mechanical Turk (MTurk).
MTurk provides access to a diverse range of respondents from both the United States and around the world. You design a short screening survey on MTurk to filter participants based on their cultural background.
Those who qualify are then invited to complete a longer survey, with bonus pay as an incentive. You can also use email notifications for qualified participants or set specific location criteria to ensure representation from collectivist or individualist cultures.
Example: Convenience Sampling of a Pre-existing Group
Imagine you’re conducting a survey on work satisfaction at a major camping gear company in your city. Although the manager supports your research, privacy rules prevent them from providing a list of all employees.
Since you lack a sampling frame for probability sampling, you opt for convenience sampling. You station yourself near the coffee machine and approach employees randomly, inviting them to participate in your brief survey.
How to minimize bias in convenience sampling?
Convenience samples are highly vulnerable to bias in research. Convenience samples never produce a statistically balanced population selection because the researcher selects the sample based on convenience rather than equal probability. Sampling bias results from this.
Participants in surveys frequently receive financial or monetary incentives in exchange for filling them out. If a reward is their primary motivation, individuals may provide incorrect or false answers. Response bias, social desirability bias, and self-selection bias result from this.
When selecting participants, researchers employ subjective methods (such as stopping the people who seem the friendliest). As a result, observer bias occurs.
Despite the limitations, researchers can take steps to reduce bias in their research. Here are some suggestions:
- To make your research replicable and reproducible, thoroughly describe in the methods section of your research paper how you recruit your participants.
- By recruiting as many participants or cases as you can, you can diversify your data collection. To get the right sample size, use a sample size calculator.
- Distribute your surveys on various days and times and employ several techniques to recruit participants.
- Use appropriate descriptive analysis methods instead of statistical analyses developed for probability samples.
- Generally, try not to overstate the results of your study. Recall that the findings drawn from a convenience sample are limited to the specific case or participant group that was chosen. They are not, by definition, applicable to the target population.
When to use convenience sampling?
- Before conducting research, gain a clear understanding of your target population. Knowing who these individuals are will help you plan where to find and engage with them.
- Larger sample sizes tend to yield more reliable results. Multiple samples can be combined to create a larger dataset, reducing the likelihood of sampling error.
- Create a well-balanced survey or questionnaire by including both qualitative and quantitative questions.
- To ensure the accuracy and consistency of your findings, consider repeating the survey.
- Convenience sampling is useful for practical reasons, such as ease of access to participants. However, it may introduce bias.
Advantages of Convenience Sampling
Here are the advantages of convenience sampling:
- Quick and Simple Data Collection: Convenience sampling is a fast and straightforward method of gathering data, making it ideal when time is limited, and minimal effort is preferred.
- Few Rules and Large Samples: Researchers favor convenience sampling because it has few restrictions, allowing them to generate large sample sizes within short timeframes.
- Cost-Effective: Convenience sampling is inexpensive since it requires minimal planning and no extensive travel. This makes it especially suitable for budget-conscious individuals, such as students.
- Easily Accessible Samples: This method often involves populations that are readily available, making data collection more accessible.
- Suitable for Pilot Studies and Hypothesis Exploration: Researchers can use convenience sampling for pilot data collection or to explore hypotheses that may be further investigated in future research.
- Scalability: Adding more participants later is effortless with convenience sampling, allowing researchers to expand their samples as needed.
Drawbacks of Convenience Sampling
Here are the drawbacks of convenience sampling:
Convenience Bias
Convenience sampling can lead to convenience bias or selection bias, where the samples collected may not accurately represent the target population. This bias can undermine the generalizability of the study’s results.
Types of bias that can result from convenience sampling include sampling bias (due to non-random selection), selection bias (due to self-selection or researcher bias), and positivity bias (where participants are more likely to provide positive responses).
Lack of External Validity
The high risk of bias in convenience sampling reduces the external validity of research findings. This means that the credibility and applicability of the results to the broader research community may be limited.