what is the best sampling technique to use for determining the average speed of the cars
What are sampling methods and how exercise yous choose the best i?
Posted on 18th November 2020 by
Tutorials and Fundamentals
This tutorial will introduce sampling methods and potential sampling errors to avoid when conducting medical inquiry.
Contents
- Introduction to sampling methods
- Examples of different sampling methods
- Choosing the best sampling method
Introduction to sampling methods
It is important to understand why we sample the population; for example, studies are built to investigate the relationships between risk factors and affliction. In other words, we want to observe out if this is a true association, while nevertheless aiming for the minimum chance for errors such equally: chance, bias or confounding.
All the same, it would not be viable to experiment on the whole population, we would need to take a good sample and aim to reduce the risk of having errors by proper sampling technique.
What is a sampling frame?
A sampling frame is a record of the target population containing all participants of interest. In other words, it is a list from which we tin can excerpt a sample.
What makes a good sample?
A good sample should be a representative subset of the population we are interested in studying, therefore, with each participant having equal take chances of beingness randomly selected into the study.
Examples of different sampling methods
Nosotros could cull a sampling method based on whether we want to account for sampling bias; a random sampling method is oft preferred over a non-random method for this reason. Random sampling examples include: uncomplicated, systematic, stratified, and cluster sampling. Non-random sampling methods are liable to bias, and common examples include: convenience, purposive, snowballing, and quota sampling. For the purposes of this blog we will exist focusing on random sampling methods.
Simple
Example: We want to conduct an experimental trial in a small-scale population such equally: employees in a company, or students in a college. Nosotros include anybody in a listing and use a random number generator to select the participants
Advantages: Generalisable results possible, random sampling, the sampling frame is the whole population, every participant has an equal probability of being selected
Disadvantages: Less precise than stratified method, less representative than the systematic method
Systematic
Case: Every nth patient entering the out-patient clinic is selected and included in our sample
Advantages: More than feasible than elementary or stratified methods, sampling frame is not always required
Disadvantages:Generalisability may subtract if baseline characteristics repeat across every nth participant
Stratified
Instance: Nosotros have a big population (a urban center) and nosotros want to ensure representativeness of all groups with a pre-adamant feature such as: age groups, indigenous origin, and gender
Advantages:Inclusive of strata (subgroups), reliable and generalisable results
Disadvantages: Does not piece of work well with multiple variables
Cluster
Example: 10 schools have the same number of students beyond the county. Nosotros can randomly select 3 out of ten schools as our clusters
Advantages: Readily achievable with nigh budgets, does non require a sampling frame
Disadvantages: Results may non be reliable nor generalisable
How can you identify sampling errors?
Not-random selection increases the probability of sampling (option) bias if the sample does non represent the population we want to study. Nosotros could avoid this by random sampling and ensuring representativeness of our sample with regards to sample size.
An inadequate sample size decreases the confidence in our results equally we may think there is no pregnant difference when actually at that place is. This blazon two mistake results from having a small sample size, or from participants dropping out of the sample.
In medical inquiry of disease, if nosotros select people with certain diseases while strictly excluding participants with other co-morbidities, we run the gamble of diagnostic purity bias where important sub-groups of the population are not represented.
Furthermore, measurement bias may occur during re-collection of risk factors past participants (recall bias) or assessment of outcome where people who live longer are associated with treatment success, when in fact people who died were non included in the sample or data analysis (survivors bias).
Choosing the all-time sampling method
Past post-obit the steps below we could choose the best sampling method for our written report in an orderly mode.
Research objectiveness
Firstly, a refined research question and goal would assist usa define our population of interest. If our calculated sample size is modest then information technology would be easier to go a random sample. If, however, the sample size is large, then nosotros should check if our budget and resources tin can handle a random sampling method.
Sampling frame availability
Secondly, we demand to check for availability of a sampling frame (Simple), if not, could nosotros make a listing of our own (Stratified). If neither choice is possible, we could yet apply other random sampling methods, for instance, systematic or cluster sampling.
Study design
Moreover, we could consider the prevalence of the topic (exposure or effect) in the population, and what would be the suitable study pattern. In addition, checking if our target population is widely varied in its baseline characteristics. For instance, a population with large ethnic subgroups could best exist studied using a stratified sampling method.
Random sampling
Finally, the best sampling method is always the one that could best reply our research question while also allowing for others to make use of our results (generalisability of results). When we cannot afford a random sampling method, we can e'er cull from the non-random sampling methods.
Conclusion
To sum up, we now sympathise that choosing betwixt random or not-random sampling methods is multifactorial. Nosotros might oft exist tempted to choose a convenience sample from the start, but that would not only decrease precision of our results, and would brand us miss out on producing research that is more robust and reliable.
References (pdf)
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Source: https://s4be.cochrane.org/blog/2020/11/18/what-are-sampling-methods-and-how-do-you-choose-the-best-one/
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