Written by Dr. Hannes Nel
Some academics and other scientists are of the opinion that the COVID-19 tests can be inaccurate by as much as 30 percent.
And there are those who believe that the mortality rates due to COVID-19 in some countries are much higher than the reported figures.
Perhaps it is true that findings and statistics are sometimes deliberately manipulated.
Then again, imagine how near impossible it must be to conduct research on an issue that affects the entire world.
Researchers often have no other choice than to make use of sampling.
And sampling facilitates efficiency and viability, not validity and accuracy.
I will discuss typical case sampling, unique-case sampling and volunteer sampling in this article.
You can use typical-case sampling when you need to collect data on general items.
A typical-case sample is composed by identifying and including people who can be regarded as typical for a community or phenomenon.
Such a sample is used to avoid information, or worse, research findings and recommendations being rejected because they have been obtained from suspect, perhaps even deviant, cases.
It can also be used to avoid using data or opinions that are politically laden or otherwise manipulated.
A typical case sample should allow you, as the researcher, to develop a profile of what would generally be agreed as being average or normal.
Typical-case samples are often useful when large communities and complex problems are investigated.
Such samples enable those who are not familiar with a community to gain an understanding of the nature of the community in a relatively short time.
Members of the community can often help you to select items for a sample by suggesting criteria for such samples.
An example of a typical-case sample is when you choose your sample from a middle-class suburb rather than from a poor or rich suburb if you wish to do research on the spending habits of a city.
The spending habits of the poor and the rich would probably not be typical for the community.
Of course, your sample will be more representative of the community if you were to include poor, middle class and rich people in your sample.
But then you would be using random sampling or systematic sampling.
In unique-case sampling, you would identify and include cases that are rare, unique or unusual in terms of one or more characteristics.
Such cases might agree with typical cases in other respects.
An example of unique-case sampling can be if you were to do research on the genetic makeup of a nation or tribe that has not been affected by die COVID-19 virus, or has been affected markedly less that the average for other countries.
As in the case of snowball sampling, you will need to take intentional steps to gain access to individuals who are difficult to establish contact with.
Also, as in the case of snowball sampling, you might need to rely on volunteers for your sample group.
Then again, most research rely on the co-operation of volunteers.
You would typically start by approaching family members, friends, friends of friends, etc.
You can also ask for volunteers by posting an advertisement in a newspaper, ask for help on social media, write letters to possible volunteers, visit managers of businesses and ask them for assistance, etc.
Making use of volunteers whom you do not know as your sample can be risky.
You often do not have any control over the validity and accuracy, authenticity or sincerity of their responses to questions or any other contributions to your research.
It will, furthermore, be rather difficult to claim that your findings apply generally if you do not know the motives or reasons why volunteers became involved in your research project.
Typical-case sampling can be used with good effect to avoid using subjective data. This is done by collecting data from a general population, items or phenomena.
Unique-case sampling is used to investigate rare, unique or unusual cases or phenomena.
In volunteer sampling people are asked to volunteer to be included in the sample.
Volunteers need to be screened to ensure that they are authentic and trustworthy.
This is my last video on sampling, Methods. Therefore, I guess it would be fitting if I were to summarise the links between the different types of sampling. Here it is:
- Cluster sampling is a form of stage sampling.
- Convenience sampling is a form of opportunistic sampling.
- Convenience sampling, dimensional sampling, quota sampling, purposive sampling and snowball sampling can be conducted as non-probability sampling.
- Extreme-case sampling is used in conjunction with most other types of sampling.
- Matched sampling and stratified sampling use systematic sampling.
- Multi-phase sampling is a form of stage sampling.
- Purposive sampling is a variant of boosted sampling.
- Reputational sampling and unique-case sampling are variants of extreme-case sampling.
- Snowball sampling is a form of volunteer sampling.
- Systematic sampling is a modified form of random sampling.
- Theoretical sampling is a form of criterion sampling and dimensional sampling.
- Time sampling includes instantaneous sampling, interval sampling and duration sampling.
- Typical-case sampling is related to case-study sampling.
- Typical-case sampling is the opposite of critical-case sampling.