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The downside is that if the samples arranged in some organized manner there is a great potential for bias in the sample selection. Moreover, because this method limits the potential for every target participant to be included in the study the external validity of the results will be limited (Robson, 2011).
Stratified sampling is a technique that can be used when there are subgroups within the target population that have attributes that may be relevant to the outcome such as different genders, different ethnic backgrounds, different levels of education, etc. (Bryman, 2012). The researcher divides the target population in the subgroups and then randomly samples from each subgroup according to some quota that has been previously identified. This allows for more realistic overall sample and can help enhance external validity; however, it is often difficult to get the information ahead of time, there may not be sufficient amounts of participants in the specific subgroups available, and this method is often time-consuming...
Here the researcher separates the natural occurring groups, such as two different first grade classes in the school, and then takes a simple random sample from each of the clusters. This makes the sampling process simpler; however, it can also limit external validity because of inherent differences between the naturally occurring groups that may affect the outcome variable. Moreover, if the naturally occurring groups are not large enough there can be issues with the findings (Robson, 2011).
The choice of the sampling method will depend on the researcher, the availability of participants, and the aims and anticipated outcomes of the study.
References
Bryman, a. (2012). Social research methods. New York: Oxford university press.
Robson, C. (2011). Real world research: a resource for users of social research methods in applied settings. Chichester, UK: Wiley.
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