By Julia Simkus, published Jan 30, 2022
Convenience sampling (also called accidental sampling or grab sampling) is a method of non-probability sampling where researchers will choose their sample based solely on the convenience.
Non-probability sampling means that researchers choose the sample as opposed to randomly selecting it, so not all members of the population have an equal chance of participating in the study.
There is little judgment or speculation when choosing the representative sample in convenience sampling; the sole selection criteria is ease of obtaining a participant.
This can be dependent on costs, geographic distributions, or facility of obtaining data. Some examples of convenience sampling could include recruiting friends to participate in your study, collecting data from locations that are nearby, sending a survey in the mail, or sharing a link on social media.
For example, if high school students are conducting a study on the average consumption of pizza in the cafeteria each week, they could call their classmates and ask how many slices they consume during the week.
- Understand who is the target population that will help your research and plan out where you could go to speak to these people.
- Take multiple samples as a larger sample size will reduce the chance of sampling error.
- Include both qualitative and quantitative questions in your survey or questionnaire.
- Repeat the survey to ensure the accuracy of your results.
- Use convenience sampling along with probability sampling to supplement your research.
Convenience sampling is beneficial when time is a constraint as it is a simple method and takes minimal effort.
Many researchers prefer convenience sampling as there are few rules to follow, and it allows researchers to generate large samples in short periods of time.
Convenience sampling has little cost involved as no travel or extensive planning is necessary. This method is particularly useful for students who are on a budget as it requires minimal cost and experience.
Convenience sampling tends to be collected with populations that are easily attainable.
As the data is readily available, researchers can use convenience sampling to conduct pilot data or explore a hypothesis that might be tested in future research.
And, if more participants need to be added at a later date, researchers can effortlessly create more samples.
Bias is the primary disadvantage of convenience sampling, and in some cases, this sole limitation can outweigh the advantages. Collected samples may not be representative of the population of interest and thus, the results cannot be generalized to a greater population.
Some examples of the types of bias that could result from convenience sampling include sampling bias, selection bias, and positivity bias.
Due to the high probability of bias in convenience sampling, your research findings will likely have little credibility in the greater research industry.
Convenience sampling is often used for qualitative research. Researchers use this sampling technique to recruit participants who are convenient and easily accessible.
For example, if a company wants to gather feedback on their new product, they could go to the local mall and approach individuals to ask for their opinion on the product.
They could have people participate in a short survey and ask questions such as ‘have you heard of x brand?’ or ‘what do you think of x product?
Because researchers are usually unable to generalize the results of the survey to the population as a whole, the estimates derived from convenience samples are often biased.
There is the possibility of over or under representation as the sample poorly represents the target population. Since subjects are selected because they are easily accessible, researchers tend to not gain a range of participants each time they collect data, and they also may exclude relevant demographic subsets from the results.
There are many strategies that researchers can use to reduce bias when convenience sampling. One of the most successful ways to reduce bias is to use convenience sampling along with probability sampling.
Probability sampling uses a random selection process so everyone in your population has an equal chance of being chosen. Using both convenience sampling and probability sampling together will enable researchers to draw accurate conclusions by reducing, or even eliminating, bias.
Other techniques to effectively convenience sample include:
Purposive sampling and convenience sampling are often used interchangeably, but they are two different methods. Researchers in convenience sampling will recruit participants based solely on convenience and accessibility.
They will leverage individuals that can be accessed with minimal effort. On the other hand, researchers in purposive sampling will use judgment and planning to select a sample of individuals that will benefit their study.
Researchers must have prior knowledge about the purpose of the study so they can choose participants that will fit certain characteristics and represent the greater population of interest.
Julia Simkus is an undergraduate student at Princeton University, majoring in Psychology. She plans to pursue a PhD in Clinical Psychology upon graduation from Princeton in 2023. Julia has co-authored two journal articles, one titled “Substance Use Disorders and Behavioral Addictions During the COVID-19 Pandemic and COVID-19-Related Restrictions," which was published in Frontiers in Psychiatry in April 2021 and the other titled “Food Addiction: Latest Insights on the Clinical Implications," to be published in Handbook of Substance Misuse and Addictions: From Biology to Public Health in early 2022.
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