As in hypothesis testing research, the concept of a population is crucial, because the population defines the set of entities from which the research sample is to be drawn. Also, selectioon of an appropriate population controls extraneous variation and helps to define the limits for generalizing the findings.

 

The cases may be chosen to replicate previous cases or extend emergent theory, or they may be chosen to fill theoretical categories and provide examples of polar types. While the cases may be chosen randomly, random selection is neither necessary, nor even preferable. Pettigrew (1988), given the limited number of cases which can usually be studies, it makes sense to choose cases such as extreme situation and polar types in which the process of interest is "transparently observable."

 

The goal of theoretical sampling is to choose cases which are likely to replicate or extend the emergent theory. In contrast, traditional, within experiment hypothesis-testing studies rely on statistical sampling, in which researchers randomly select the sample from the population. The goal of sampling is here to obtain accurate statistical evidence on the distrubutions of variables within the population.

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