Judgement sampling has the advantage of being time-and cost-effective to perform whilst resulting in a range of responses particularly useful in qualitative research. However, in addition to volunteer bias, it is also prone to errors of judgement by the researcher and the findings, whilst being potentially broad, will not necessarily be representative. This method is commonly used in social sciences when investigating hard-to-reach groups. Existing subjects are asked to nominate further subjects known to them, so the sample increases in size like a rolling snowball.
For example, when carrying out a survey of risk behaviours amongst intravenous drug users, participants may be asked to nominate other users to be interviewed. Snowball sampling can be effective when a sampling frame is difficult to identify. However, by selecting friends and acquaintances of subjects already investigated, there is a significant risk of selection bias choosing a large number of people with similar characteristics or views to the initial individual identified.
There are five important potential sources of bias that should be considered when selecting a sample, irrespective of the method used. Sampling bias may be introduced when: 1.
Skip to main content. Create new account Request new password. You are here 1a - Epidemiology. Probability Sampling Methods 1. Simple random sampling In this case each individual is chosen entirely by chance and each member of the population has an equal chance, or probability, of being selected. Systematic sampling Individuals are selected at regular intervals from the sampling frame. Stratified sampling In this method, the population is first divided into subgroups or strata who all share a similar characteristic.
Clustered sampling In a clustered sample, subgroups of the population are used as the sampling unit, rather than individuals. Non-Probability Sampling Methods 1. Convenience sampling Convenience sampling is perhaps the easiest method of sampling, because participants are selected based on availability and willingness to take part. Quota sampling This method of sampling is often used by market researchers.
Judgement or Purposive Sampling Also known as selective, or subjective, sampling, this technique relies on the judgement of the researcher when choosing who to ask to participate. Snowball sampling This method is commonly used in social sciences when investigating hard-to-reach groups.
Bias in sampling There are five important potential sources of bias that should be considered when selecting a sample, irrespective of the method used. Our most popular content Public Health Textbook. Identifying and managing internal and external stakeholder interests.
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In medical research of disease, if we select people with certain diseases while strictly excluding participants with other co-morbidities, we run the risk 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 by participants recall bias or assessment of outcome where people who live longer are associated with treatment success, when in fact people who died were not included in the sample or data analysis survivors bias.
By following the steps below we could choose the best sampling method for our study in an orderly fashion. Firstly, a refined research question and goal would help us define our population of interest.
If our calculated sample size is small then it would be easier to get a random sample. If, however, the sample size is large, then we should check if our budget and resources can handle a random sampling method.
Secondly, we need to check for availability of a sampling frame Simple , if not, could we make a list of our own Stratified. If neither option is possible, we could still use other random sampling methods, for instance, systematic or cluster sampling. Moreover, we could consider the prevalence of the topic exposure or outcome in the population, and what would be the suitable study design.
In addition, checking if our target population is widely varied in its baseline characteristics. For example, a population with large ethnic subgroups could best be studied using a stratified sampling method. Finally, the best sampling method is always the one that could best answer 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 always choose from the non-random sampling methods. To sum up, we now understand that choosing between random or non-random sampling methods is multifactorial. We might often be tempted to choose a convenience sample from the start, but that would not only decrease precision of our results, and would make us miss out on producing research that is more robust and reliable. Your email address will not be published.
Oversimplified info on sampling methods. Probabilistic of the sampling and sampling of samples by chance does rest solely on the random methods. Factors such as the random visits or presentation of the potential participants at clinics or sites could be sufficiently random in nature and should be used for the sake of efficiency and feasibility.
In this case, as a sample is formed based on specific attributes, the created sample will have the same qualities found in the total population. It is a rapid method of collecting samples. Uses of non-probability sampling Non-probability sampling is used for the following: Create a hypothesis: Researchers use the non-probability sampling method to create an assumption when limited to no prior information is available. This method helps with the immediate return of data and builds a base for further research.
Exploratory research: Researchers use this sampling technique widely when conducting qualitative research, pilot studies, or exploratory research. Budget and time constraints: The non-probability method when there are budget and time constraints, and some preliminary data must be collected. Since the survey design is not rigid, it is easier to pick respondents at random and have them take the survey or questionnaire.
How do you decide on the type of sampling to use? Jot down the research goals. Generally, it must be a combination of cost, precision, or accuracy. Identify the effective sampling techniques that might potentially achieve the research goals.
Test each of these methods and examine whether they help in achieving your goal. Select the method that works best for the research. Select your respondents Difference between probability sampling and non-probability sampling methods We have looked at the different types of sampling methods above and their subtypes. To encapsulate the whole discussion, though, the significant differences between probability sampling methods and non-probability sampling methods are as below: Probability Sampling Methods Non-Probability Sampling Methods Definition Probability Sampling is a sampling technique in which samples from a larger population are chosen using a method based on the theory of probability.
Alternatively Known as Random sampling method. Non-random sampling method Population selection The population is selected randomly.
The population is selected arbitrarily. Nature The research is conclusive. The research is exploratory. Sample Since there is a method for deciding the sample, the population demographics are conclusively represented. Since the sampling method is arbitrary, the population demographics representation is almost always skewed. Time Taken Takes longer to conduct since the research design defines the selection parameters before the market research study begins.
This type of sampling method is quick since neither the sample or selection criteria of the sample are undefined. Results This type of sampling is entirely unbiased and hence the results are unbiased too and conclusive. This type of sampling is entirely biased and hence the results are biased too, rendering the research speculative. Hypothesis In probability sampling, there is an underlying hypothesis before the study begins and the objective of this method is to prove the hypothesis.
In non-probability sampling, the hypothesis is derived after conducting the research study. Related Posts. Sampling bias in research, types, examples, and how to avoid it. A guide to choosing the right sample partner for research. Create online polls, distribute them using email and multiple other options and start analyzing poll results. Research Edition LivePolls. Features Comparison Qualtrics Explore the list of features that QuestionPro has compared to Qualtrics and learn how you can get more, for less.
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