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Every researcher strives to carry out research that can be generalised to their target population. To be 100% confident in this, they would need to carry out their research on everyone who fits the bill. However, in most cases, this is next to impossible to do. So instead, they draw an appropriate sample after identifying the target population of their…
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Jetzt kostenlos anmeldenEvery researcher strives to carry out research that can be generalised to their target population. To be 100% confident in this, they would need to carry out their research on everyone who fits the bill. However, in most cases, this is next to impossible to do. So instead, they draw an appropriate sample after identifying the target population of their research. But how do they know who to include in the sample? This is why sampling frames need to be understood.
Let's start by learning what exactly is meant by sampling frame.
After identifying a target population in research, you can use a sample frame to draw a representative sample for your research.
A sampling frame refers to a list or a source that includes every individual from your entire population of interest and should exclude anyone not part of the target population.
Sample frames should be systematically organised, so all the sampling units and information can be easily found.
If you are investigating the consumption of energy drinks by student-athletes in your school, your population of interest is all student-athletes at that school. What should your sampling frame include?
Information such as names, contact information and sport played by every student-athlete attending your school would be useful.
No student-athlete should be omitted from the sampling frame, and no non-athletes should be included. Having a list like this allows you to draw a sample for your study using a sampling method of your choice.
Fig. 1 - Sampling frames help to stay organised when handling a large sample population.
Sampling is a vital part of the research; it refers to selecting a group of participants from a larger population of interest. If we want to generalise the research findings to a specific population, our sample must be representative of that population.
Choosing the right sampling frame is an important step in ensuring that.
Representative vs unrepresentative samples
Suppose the population of interest is the population of the United Kingdom. In that case, the sample should reflect the characteristics of this population. A sample consisting of 80% white male college students from England doesn't reflect the characteristics of the entire UK population. Therefore it is not representative.
Sampling frames are important for researchers to stay organised and ensure that the most up-to-date information for a population is being used. This can cut down time when recruiting participants during research.
One type of sampling frame we already talked about is lists. We can create lists of schools, households or employees in a company.
Suppose your target population is everyone living in London. In that case, you might use census data, telephone directory or data from an electoral register to select a subset of people for your research.
And another type of sampling frame is area frames, which include land units (e.g. cities or villages) from which you can draw samples. Area frames can use satellite images or a list of different areas.
You can also use satellite images to identify households in different areas of London that can serve as your sample frame. In this way, your sampling frame can perhaps more accurately account for people living in London even if they are not registered to vote, are not on the telephone directory, or recently moved in.
A sampling frame is the database of everyone in your target population. Your population is likely large, and maybe you can't afford to include everyone in your research, or most likely, it's just not possible.
If this is the case, researchers can use the sampling process to select a smaller group from the population that is representative. This is the group from which you collect data.
An example sampling method is random sampling.
If your sampling frame includes 1200 individuals, you can randomly select (e.g. by using a random number generator) 100 people on that list to contact and ask to participate in your research.
As previously mentioned, sampling frames allow researchers to be organised when recruiting participants.
Researchers carrying out road safety research want to reach people who regularly drive, cycle or walk in the local city.
Having three sampling frames of people who either drive, cycle or walk makes contacting people in each sample easier when recruiting participants so that there can be the same amount of people in each sample group.
While mainly useful, there are some challenges in using sampling frames in research.
Several problems can appear when using sample frames.
Not everyone is on the telephone directory or the electoral register. Similarly, not everyone whose data is on these databases still lives where they might be registered.
The number of housing units in town frequently visited by tourists might not reflect the number of households living there all year round.
If someone is registered to vote in two different cities, they will be included twice in a sampling frame consisting of voters.
Fig 3. - People can stop participating as part of a sample group at any time, which can cause issues in research.
A sampling frame is a source (e.g. a list) that includes all sampling units - all members of your target population. If your target population is the population of the UK, data from a census can be an example sampling frame.
Sampling frames are used to draw the samples for research. Having a list of everyone in your target population allows you to draw a sample for your study using a sampling method.
Types of sampling frames include frame lists and area frames.
The purpose of a sampling frame is to collect and organise all sampling units from which you can draw a sample.
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