Purposeful Sampling And Saturation
What is a good sample in qualitative research? It is NOT about size or generalizability.
The answer lies in how clearly you articulate the criteria for selecting data sources; (b) your ability to purposefully select cases; and (c) the extent to which those cases are “information-rich… for in-depth study” (Patton, 2015, p. 264) with respect to the purpose of the study.
As you prepare for this week’s Discussion, consider turning your attention to the variety of purposeful sampling strategies you may consider in developing your research plan. Also consider that qualitative researchers seek a threshold or cut-off point for when to stop collecting data. There is no magic number (although there are guidelines). Rather, saturation occurs as an interface between the researcher and the data and (b) between data collection and data analysis to determine when enough is enough.
For this Discussion, you will critique a sampling strategy used in a research article.
To prepare for this Discussion:
Review the Yob and Brewer article (attached)
POST:
Prepare a critique of the sampling strategy used by Yob and Brewer (n.d.). Include the following your critique:
1. Purpose of the Yob and Brewer Study: the purpose of the study
2. Research Questions Used by Yob and Brewer (if they are not included please infer and create RQs):
3. Site Selection (where the study took place)Site selection
4. Type of Sampling Yob and Brewer Used: The type of purposeful sampling strategy the researchers applied. (Note: Use Table 4.3 in the Ravitch & Carl text or from Patton’s Chapter 5 to identify and describe the strategy that you think best fits what they described.)
5. An Alternative Sampling Strategy Yob and Brewer Could Have Used: An alternative sampling strategy that the researchers could have considered. Explain your choice in terms of how the strategy is consistent with their research purpose and criteria for selecting cases.
6. Data Saturation Definition (below, I gave it to you above. You can use it.) Provide a data saturation definition and evaluate the work of the researchers in this article regarding their efforts to achieve data saturation. Note what the researchers could have done differently to convince you that the relevant and important themes emerged.
ATTENTION: Please note that data saturation and thematic saturation are completely different. One or more of your authors use the terms interchangeably. They are not the same. Data saturation: this is when no additional data will produce any new information. Data saturation occurs at around 6 participants in the majority of studies. Some studies that require a diverse sample may need a slightly larger sample. An example would be that after 6 interviews you kept hearing the same responses to questions. You have achieved data saturation. Data saturation occurs during interviews. Thematic saturation: this is when no additional data will produce any new themes. Thematic saturation occurs at around 12 participants. Some studies that require a diverse sample may require more participants for this to occur. An example would be that as you analyzed your data you found that no new themes emerged. Thematic saturation occurs at the analysis stage.
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