Convenience sampling is a non-probability sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher.
The subjects are selected just because they are easiest to recruit for the study and the researcher did not consider selecting subjects that are representative of the entire population.
In all forms of research, it would be ideal to test the entire population, but in most cases, the population is just too large that it is impossible to include every individual. This is the reason why most researchers rely on sampling techniques like convenience sampling, the most common of all sampling techniques. Many researchers prefer this sampling technique because it is fast, inexpensive, easy and the subjects are readily available.
One of the most common examples of convenience sampling is using student volunteers as subjects for the research. Another example is using subjects that are selected from a clinic, a class or an institution that is easily accessible to the researcher. A more concrete example is choosing five people from a class or choosing the first five names from the list of patients.
In these examples, the researcher inadvertently excludes a great proportion of the population. A convenience sample is either a collection of subjects that are accessible or a self selection of individuals willing to participate which is exemplified by your volunteers.
Researchers use convenience sampling not just because it is easy to use, but because it also has other research advantages.
This sampling technique is also useful in documenting that a particular quality of a substance or phenomenon occurs within a given sample. Such studies are also very useful for detecting relationships among different phenomena.
The most obvious criticism about convenience sampling is sampling bias and that the sample is not representative of the entire population. This may be the biggest disadvantage when using a convenience sample because it leads to more problems and criticisms.
Systematic bias stems from sampling bias. This refers to a constant difference between the results from the sample and the theoretical results from the entire population. It is not rare that the results from a study that uses a convenience sample differ significantly with the results from the entire population. A consequence of having systematic bias is obtaining skewed results.
Another significant criticism about using a convenience sample is the limitation in generalization and inference making about the entire population. Since the sample is not representative of the population, the results of the study cannot speak for the entire population. This results to a low external validity of the study.
When using convenience sampling, it is necessary to describe how your sample would differ from an ideal sample that was randomly selected. It is also necessary to describe the individuals who might be left out during the selection process or the individuals who are overrepresented in the sample.
In connection to this, it is better if you can describe the possible effects of the people who were left out or the subjects that are overrepresented to your results. This will allow the readers of your research to get a good grasp of the sample that you were testing. It will also enable them to estimate the possible difference between your results and the results from the entire population.